f

MUSIC and DOA Estimation

```Hi,

In the literature, there is a common claim made that the performance
of MUSIC for direction of arrival estimation (DOA) is affected when
the wrong number of directional sources is assumed. There is no
argument presented to support this claim, nor any references given,
just the claim.

I am curious what the basis for this claim is. Although there are a
variety of MUSIC-like methods and a this topic can get complicated,
overall, it seems pretty fair to say that when you underestimate the
number of sources, it is due to the presence of sources whose signals
are weak (relative to the noise floor). In this case, the error would
seem to be conservative and not affect the performance of MUSIC much
(since the remaining signal subspace will still span the array
manifold of the sources which are counted as being present). If you
were using Spectral MUSIC, you would have more noise evrs to take the
projection with (which is not a bad thing) and if you were using ROOT-
MUSIC, the roots of the signals counted as being present would not be
affected either. If you overestimate the number of sources, this would
not be a problem for Spectral MUSIC, since the signal subspace will
span the subspace of the steering vectors for the sources which are
actually present. The only problem I can see is with ROOT-MUSIC, where
if you factor a root from a spurious source, it will affect the
subsequent roots of the actual sources present.

Does this reasoning sound like the justification for the claim about
MUSIC I presented, or is there something else I am missing?

TIA,

Matt

If one is using MUSIC, it would seem reasonable to assume that one is
probably using some information theoretic method (such as the MDL or
AIC) to estimate the number of sources. Now suppose that the number of
directional sources is mis-estimated. The three major sources I can
see that would contribute to the mis-estimation are:
1) You have correlated signals
2) Directional sources are missed because their signals are weak
(relative to the noise floor)
3) Spurious directional sources are counted (due to the fact that
MUSIC sometimes
```
 0
6/13/2009 7:33:24 PM
comp.dsp 20333 articles. 1 followers. allnor (8509) is leader.

16 Replies
415 Views

Similar Articles

[PageSpeed] 5

```On 13 Jun, 21:33, junoexpress <MTBrenne...@gmail.com> wrote:
> Hi,
>
> In the literature, there is a common claim made that the performance
> of MUSIC for direction of arrival estimation (DOA) is affected when
> the wrong number of directional sources is assumed. There is no
> argument presented to support this claim, nor any references given,
> just the claim.

The claims may or may not be true, depending on exactly
how  they are phrased. Do you have any pointers to where

> I am curious what the basis for this claim is. Although there are a
> variety of MUSIC-like methods and a this topic can get complicated,
> overall, it seems pretty fair to say that when you underestimate the
> number of sources, it is due to the presence of sources whose signals
> are weak (relative to the noise floor). In this case, the error would
> seem to be conservative and not affect the performance of MUSIC much
> (since the remaining signal subspace will still span the array
> manifold of the sources which are counted as being present). If you
> were using Spectral MUSIC, you would have more noise evrs to take the
> projection with (which is not a bad thing) and if you were using ROOT-
> MUSIC, the roots of the signals counted as being present would not be
> affected either. If you overestimate the number of sources, this would
> not be a problem for Spectral MUSIC, since the signal subspace will
> span the subspace of the steering vectors for the sources which are
> actually present. The only problem I can see is with ROOT-MUSIC, where
> if you factor a root from a spurious source, it will affect the
> subsequent roots of the actual sources present.

There are several causes for inaccuracies in the MUSIC-type
estimators. One is the SNR, others are related to wrong order
estimates, like if there in reality are 4 signals present,
but the order estimator only finds 3 of them. In such cases,
it is likely that at least some of the DoAs are off, either
because the SNR is low or the 'missing' signal lies very close
to one of the others. If the 'missing' signal has a significantly
smaller amplitude than the others, the remaining DoA estimates
might be accurate anyway.

> Does this reasoning sound like the justification for the claim about
> MUSIC I presented, or is there something else I am missing?

Yes, there is.

MUSIC-type estimators (meaning all estimators which
implicitly or explicitly use a covariance matrix of
order P to estimate the parameters of D signals) *fail*
*unconditionally* when D >=P.

Just try it and see: Use your favourite MUSIC implementation
and specify it to run with a covariance matrix of order P.
Simulate a noise-free signal with N = 3P samples (to make
sure the covariance matrix is well-behaved) as follows:

First use *one* sinusoidal with DoA cos(phi_1) = 2*pi*1/P.
Use your MUSIC estimator and verify that you find the
DoA to within numerical precision (remember, noise-free
signal).

Next, *add* a signal component with the same amplitude
and with DoA cos(phi_2) = 2*pi*2/P. Repeat the MUSIC
analysis to verify that you find the two DoAs.

*Add* successive signals with DoAs cos(phi_n) = 2*pi*n/P
for n=3,4,...,2P. Make sure the signals have the same

Just to be clear: The first time around the noise-free
signal contains one sinusoidal. The scond time it contains
two sinusodials. The n'th time it contains n sinusoidals.

At some point, either near n = P/2 or near n=P (the
details depend a bit on your MUSIC implementation and
if you use real-valued or complex-valued signals),
the DoA estimates break down. This is because the
number of signal components becomes as large as the
dimension of the column space of the signal covariance
matrix. Once that happens, the rank of the null space
is 0 (it needs to be at least 1 for MUSIC to work),
so MUSIC breaks down.

If you want to, repeat the excercise with various SNRs,
and with different MUSIC implementations.

Rune
```
 0
allnor (8509)
6/13/2009 8:00:15 PM
```On 13 Jun, 22:00, Rune Allnor <all...@tele.ntnu.no> wrote:

> Just try it and see: Use your favourite MUSIC implementation
> and specify it to run with a covariance matrix of order P.
> Simulate a noise-free signal with N = 3P samples (to make
> sure the covariance matrix is well-behaved) as follows:
>
> First use *one* sinusoidal with DoA cos(phi_1) = 2*pi*1/P.
> Use your MUSIC estimator and verify that you find the
> DoA to within numerical precision (remember, noise-free
> signal).
>
> Next, *add* a signal component with the same amplitude
> and with DoA cos(phi_2) = 2*pi*2/P. Repeat the MUSIC
> analysis to verify that you find the two DoAs.
>
> *Add* successive signals with DoAs cos(phi_n) = 2*pi*n/P
> for n=3,4,...,2P. Make sure the signals have the same
> amplitudes, and add *no* noise.
>
> Just to be clear: The first time around the noise-free
> signal contains one sinusoidal. The scond time it contains
> two sinusodials. The n'th time it contains n sinusoidals.

Sorry, I got the DoAs wrong: Use a DoA for the n'th
signal as

cos(phi_n) = pi*n/P     (deleted factor 2).

Rune
```
 0
allnor (8509)
6/13/2009 8:03:01 PM
```On Jun 13, 4:00=A0pm, Rune Allnor <all...@tele.ntnu.no> wrote:
> On 13 Jun, 21:33, junoexpress <MTBrenne...@gmail.com> wrote:
>
> > Hi,
>
> > In the literature, there is a common claim made that the performance
> > of MUSIC for direction of arrival estimation (DOA) is affected when
> > the wrong number of directional sources is assumed. There is no
> > argument presented to support this claim, nor any references given,
> > just the claim.
>
> The claims may or may not be true, depending on exactly
> how =A0they are phrased. Do you have any pointers to where
>
This claim is found in a good many papers on the topic of signal
enumeration. Two that make the statement clearly are:
1) IEEE Trans Acc, Speech, and Signal Processing, vol. 38, no. 11,
1990
"On Information Theoretic Criteria...." by Wong, Zhang, Reilly, and
Yip
(see text after eqn 5 in article)
2) IEEE Trans Signal Processing, vol. 39, no. 8, 1991
"A Parametric Method for Determining the Number of Signals in Narrow-
Band Direction Finding"
by Wu and Fuhrman (see first paragraph)

>
>
>
> There are several causes for inaccuracies in the MUSIC-type
> estimators. One is the SNR, others are related to wrong order
> estimates, like if there in reality are 4 signals present,
> but the order estimator only finds 3 of them. In such cases,
> it is likely that at least some of the DoAs are off, either
> because the SNR is low or the 'missing' signal lies very close
> to one of the others. If the 'missing' signal has a significantly
> smaller amplitude than the others, the remaining DoA estimates
> might be accurate anyway.
>
Your line of reasoning is pretty much what makes me doubt this claim.
A source that is missed, is most likely missed because its SNR is very
small. The components of the stronger sources on the evr that gets
dropped from the signal subspace and gets put into the noise sub-space
cannot be that large, so when you run say Spectral MUSIC, the location
where the reciprocal of the projection of the steering vectors onto
the noise subspace has its max value should not change appreciably.

>
> > Does this reasoning sound like the justification for the claim about
> > MUSIC I presented, or is there something else I am missing?
>
> Yes, there is.
>
> MUSIC-type estimators (meaning all estimators which
> implicitly or explicitly use a covariance matrix of
> order P to estimate the parameters of D signals) *fail*
> *unconditionally* when D >=3DP.
>
The noise in the system (i.e. AWGN in the channels) will guarantee
that the covariance matrix has full rank. This condition is certainly
satisfied in all of the professional treatments of MUSIC you see in
the lit.
I am assuming the are are less sources than antennas here.
And there are other problems of course that could arise (such as the
presence of correlated sources, or an array whose antenna spacings are
greater than half a wavelength, or signals which are wide-band, etc
which will also act to screw up MUSIC), but neither I, nor the
articles to which I am referring, assume any of these conditions hold.
>
> If you want to, repeat the excercise with various SNRs,
> and with different MUSIC implementations.
>
Been there, done that.

> Rune

Thanks for your input Rune. It seems that you're the only person who
responds to array signal processing questions. I kinda thought there
would be some people on the group who could understand this stuff.
Maybe few professionals post here or are in another group.

TA,

Matt
```
 0
6/14/2009 3:30:30 AM
```On 14 Jun, 05:30, Junoexpress <MTBrenne...@gmail.com> wrote:
> On Jun 13, 4:00=A0pm, Rune Allnor <all...@tele.ntnu.no> wrote:> On 13 Jun=
, 21:33, junoexpress <MTBrenne...@gmail.com> wrote:
>
> > > Hi,
>
> > > In the literature, there is a common claim made that the performance
> > > of MUSIC for direction of arrival estimation (DOA) is affected when
> > > the wrong number of directional sources is assumed. There is no
> > > argument presented to support this claim, nor any references given,
> > > just the claim.
>
> > The claims may or may not be true, depending on exactly
> > how =A0they are phrased. Do you have any pointers to where
> > such claims are made?
>
> This claim is found in a good many papers on the topic of signal
> enumeration. Two that make the statement clearly are:
> 1) IEEE Trans Acc, Speech, and Signal Processing, vol. 38, no. 11,
> 1990
> "On Information Theoretic Criteria...." by Wong, Zhang, Reilly, and
> Yip
> (see text after eqn 5 in article)
> 2) IEEE Trans Signal Processing, vol. 39, no. 8, 1991
> "A Parametric Method for Determining the Number of Signals in Narrow-
> Band Direction Finding"
> by Wu and Fuhrman (see first paragraph)
>
>
>
> > There are several causes for inaccuracies in the MUSIC-type
> > estimators. One is the SNR, others are related to wrong order
> > estimates, like if there in reality are 4 signals present,
> > but the order estimator only finds 3 of them. In such cases,
> > it is likely that at least some of the DoAs are off, either
> > because the SNR is low or the 'missing' signal lies very close
> > to one of the others. If the 'missing' signal has a significantly
> > smaller amplitude than the others, the remaining DoA estimates
> > might be accurate anyway.
>
> Your line of reasoning is pretty much what makes me doubt this claim.
> A source that is missed, is most likely missed because its SNR is very
> small.

Not necesarily. There can be any number of reasons why a
source is missed. Small SNR is just one of them.

There is one aspect of order estimators you need to be
aware of: For AR models, order estimators are formally
are derived from statistical analyses of the reflection
coefficients that represent signal residuals during the
Levinson recursion.

MUSIC can not be represented as a Levinson recursion,
it's based on eigenvector decompositions. So the *formal*
statistical analysis, which works on the reflection
coefficients, don't work with the eigenvalues.

Now, this does *not* mean that oprder estimators do not
work with eigenvector decompositions - they do. It means
that one has bodged a tool to work in a context it was
not designed for. Which also goes a long way to explain
why order estimates might be off from time to time, with
no apparent reason.

> The components of the stronger sources on the evr that gets
> dropped from the signal subspace and gets put into the noise sub-space
> cannot be that large, so when you run say Spectral MUSIC,

Spectral MUSIC is...? If you are talking about the MUSIC
pseudo spectrum, keep in mind that there is no information
about the signal spectrum encoded in the pseudo spectrum.

> the location
> where the reciprocal of the projection of the steering vectors onto
> the noise subspace has its max value should not change appreciably.

Remember, you are working D-manifolds in an P-dimensional
complex-valued vector space. Don't expect your intuition
to be of the best help...

>
> > > Does this reasoning sound like the justification for the claim about
> > > MUSIC I presented, or is there something else I am missing?
>
> > Yes, there is.
>
> > MUSIC-type estimators (meaning all estimators which
> > implicitly or explicitly use a covariance matrix of
> > order P to estimate the parameters of D signals) *fail*
> > *unconditionally* when D >=3DP.
>
> The noise in the system (i.e. AWGN in the channels) will guarantee
> that the covariance matrix has full rank. This condition is certainly
> satisfied in all of the professional treatments of MUSIC you see in
> the lit.

You need to think one step further: The basis for the
noise subspace needs to be of rank at least 1 for MUSIC
and friends to work. Once you have a signal that contains
P (or P/2) or more sinusoidals, this no longer holds and
MUSIC fails unconditionally.

> I am assuming the are are less sources than antennas here.

You can certainly do that for academic purposes. That's
a very stupid thing to do in the real world.

> And there are other problems of course that could arise (such as the
> presence of correlated sources, or an array whose antenna spacings are
> greater than half a wavelength, or signals which are wide-band, etc
> which will also act to screw up MUSIC),

Most of those can be handled. Tedious, but not very
difficult.

> but neither I, nor the
> articles to which I am referring, assume any of these conditions hold.
>
> > If you want to, repeat the excercise with various SNRs,
> > and with different MUSIC implementations.
>
> Been there, done that.
>
> > Rune
>
> Thanks for your input Rune. It seems that you're the only person who
> responds to array signal processing questions. I kinda thought there
> would be some people on the group who could understand this stuff.

I am sure there are.

> Maybe few professionals post here or are in another group.

yourself: they just don't want to learn about the
pathological shortfalls of these types of methods.

The 'professionals' - people who work for DSP for a living
in the real world - just don't use MUSIC. For the very
reasons I've done my best to point out for you. If you don't
believe me, just look around for yourself and try and find
out how many real-world applications actually use these
sorts of methods.

There aren't too many - I'm not aware of a single one.

Rune
```
 0
allnor (8509)
6/14/2009 10:23:51 AM
```On 13 Jun, 22:03, Rune Allnor <all...@tele.ntnu.no> wrote:
> On 13 Jun, 22:00, Rune Allnor <all...@tele.ntnu.no> wrote:
>
>
>
>
>
> > Just try it and see: Use your favourite MUSIC implementation
> > and specify it to run with a covariance matrix of order P.
> > Simulate a noise-free signal with N =3D 3P samples (to make
> > sure the covariance matrix is well-behaved) as follows:
>
> > First use *one* sinusoidal with DoA cos(phi_1) =3D 2*pi*1/P.
> > Use your MUSIC estimator and verify that you find the
> > DoA to within numerical precision (remember, noise-free
> > signal).
>
> > Next, *add* a signal component with the same amplitude
> > and with DoA cos(phi_2) =3D 2*pi*2/P. Repeat the MUSIC
> > analysis to verify that you find the two DoAs.
>
> > *Add* successive signals with DoAs cos(phi_n) =3D 2*pi*n/P
> > for n=3D3,4,...,2P. Make sure the signals have the same
> > amplitudes, and add *no* noise.
>
> > Just to be clear: The first time around the noise-free
> > signal contains one sinusoidal. The scond time it contains
> > two sinusodials. The n'th time it contains n sinusoidals.
>
> Sorry, I got the DoAs wrong: Use a DoA for the n'th
> signal as
>
> cos(phi_n) =3D pi*n/P =A0 =A0 (deleted factor 2).
>
> Rune

You might want to use

cos(phi_n) =3D pi*n/2P.

This ensures that all 2P signal components are in
the [0,pi] range.
```
 0
6/14/2009 11:14:50 AM
```On Jun 14, 6:23=A0am, Rune Allnor <all...@tele.ntnu.no> wrote:
> On 14 Jun, 05:30, Junoexpress <MTBrenne...@gmail.com> wrote:
>
>
>
> > On Jun 13, 4:00=A0pm, Rune Allnor <all...@tele.ntnu.no> wrote:> On 13 J=
un, 21:33, junoexpress <MTBrenne...@gmail.com> wrote:
>
> > > > Hi,
>
> > > > In the literature, there is a common claim made that the performanc=
e
> > > > of MUSIC for direction of arrival estimation (DOA) is affected when
> > > > the wrong number of directional sources is assumed. There is no
> > > > argument presented to support this claim, nor any references given,
> > > > just the claim.
>
> > > The claims may or may not be true, depending on exactly
> > > how =A0they are phrased. Do you have any pointers to where
> > > such claims are made?
>
> > This claim is found in a good many papers on the topic of signal
> > enumeration. Two that make the statement clearly are:
> > 1) IEEE Trans Acc, Speech, and Signal Processing, vol. 38, no. 11,
> > 1990
> > "On Information Theoretic Criteria...." by Wong, Zhang, Reilly, and
> > Yip
> > (see text after eqn 5 in article)
> > 2) IEEE Trans Signal Processing, vol. 39, no. 8, 1991
> > "A Parametric Method for Determining the Number of Signals in Narrow-
> > Band Direction Finding"
> > by Wu and Fuhrman (see first paragraph)
>
> > > There are several causes for inaccuracies in the MUSIC-type
> > > estimators. One is the SNR, others are related to wrong order
> > > estimates, like if there in reality are 4 signals present,
> > > but the order estimator only finds 3 of them. In such cases,
> > > it is likely that at least some of the DoAs are off, either
> > > because the SNR is low or the 'missing' signal lies very close
> > > to one of the others. If the 'missing' signal has a significantly
> > > smaller amplitude than the others, the remaining DoA estimates
> > > might be accurate anyway.
>
> > Your line of reasoning is pretty much what makes me doubt this claim.
> > A source that is missed, is most likely missed because its SNR is very
> > small.
>
> Not necesarily. There can be any number of reasons why a
> source is missed. Small SNR is just one of them.
>
> There is one aspect of order estimators you need to be
> aware of: For AR models, order estimators are formally
> are derived from statistical analyses of the reflection
> coefficients that represent signal residuals during the
> Levinson recursion.
>
> MUSIC can not be represented as a Levinson recursion,
> it's based on eigenvector decompositions. So the *formal*
> statistical analysis, which works on the reflection
> coefficients, don't work with the eigenvalues.
>
> Now, this does *not* mean that oprder estimators do not
> work with eigenvector decompositions - they do. It means
> that one has bodged a tool to work in a context it was
> not designed for. Which also goes a long way to explain
> why order estimates might be off from time to time, with
> no apparent reason.
>
If you consider this from a math point of view, the basic fact is that
the notion of a "signal subspace" and a "noise subspace" are fiction.
point of view is not well understood, and probably should be
investigated more.

> > The components of the stronger sources on the evr that gets
> > dropped from the signal subspace and gets put into the noise sub-space
> > cannot be that large, so when you run say Spectral MUSIC,
>
> Spectral MUSIC is...? If you are talking about the MUSIC
> pseudo spectrum, keep in mind that there is no information
> about the signal spectrum encoded in the pseudo spectrum.
>
There are two basic types of MUSIC: "spectral" MUSIC (which is what
was originally proposed by Schmidt) and "ROOT" MUSIC (which is a
simple extension of spectral MUSIC that works a bit better).
Estimates about the source AOAs can be made (if again we make a boat-
load full of assumptions ;>)) from both.

> > the location
> > where the reciprocal of the projection of the steering vectors onto
> > the noise subspace has its max value should not change appreciably.
>
> Remember, you are working D-manifolds in an P-dimensional
> complex-valued vector space. Don't expect your intuition
> to be of the best help...
>
>
>
> > > No easy answers.
>
> > > > Does this reasoning sound like the justification for the claim abou=
t
> > > > MUSIC I presented, or is there something else I am missing?
>
> > > Yes, there is.
>
> > > MUSIC-type estimators (meaning all estimators which
> > > implicitly or explicitly use a covariance matrix of
> > > order P to estimate the parameters of D signals) *fail*
> > > *unconditionally* when D >=3DP.
>
> > The noise in the system (i.e. AWGN in the channels) will guarantee
> > that the covariance matrix has full rank. This condition is certainly
> > satisfied in all of the professional treatments of MUSIC you see in
> > the lit.
>
> You need to think one step further: The basis for the
> noise subspace needs to be of rank at least 1 for MUSIC
> and friends to work. Once you have a signal that contains
> P (or P/2) or more sinusoidals, this no longer holds and
> MUSIC fails unconditionally.
>
> > I am assuming the are are less sources than antennas here.
>
> You can certainly do that for academic purposes. That's
> a very stupid thing to do in the real world.
>
Not really. In many applications the cost of the array alone prohibits
you from using a large array size and you have to make that
assumption.

> > And there are other problems of course that could arise (such as the
> > presence of correlated sources, or an array whose antenna spacings are
> > greater than half a wavelength, or signals which are wide-band, etc
> > which will also act to screw up MUSIC),
>
> Most of those can be handled. Tedious, but not very
> difficult.
>
> > but neither I, nor the
> > articles to which I am referring, assume any of these conditions hold.
>
> > > If you want to, repeat the excercise with various SNRs,
> > > and with different MUSIC implementations.
>
> > Been there, done that.
>
> > > Rune
>
> > Thanks for your input Rune. It seems that you're the only person who
> > responds to array signal processing questions. I kinda thought there
> > would be some people on the group who could understand this stuff.
>
> I am sure there are.
>
> > Maybe few professionals post here or are in another group.
>
> yourself: they just don't want to learn about the
> pathological shortfalls of these types of methods.
>
Unfortunately, there are people on both sides of the fence who are
biased and insecure, which really does make it difficult for the two
sides to communicate in a meaningful and respectful manner. But I'm
sure neither of us wants to contribute to such counter-productive
exchanges. I know that I don't. Personally I find the real-life
problems you' re talking about exciting and I do think they have to be
addressed to get a real understanding of how things work.

> The 'professionals' - people who work for DSP for a living
> in the real world - just don't use MUSIC. For the very
> reasons I've done my best to point out for you. If you don't
> believe me, just look around for yourself and try and find
> out how many real-world applications actually use these
> sorts of methods.
>
> There aren't too many - I'm not aware of a single one.
>
> Rune

Good to hear: that's what keeps me in business. ;>)

M
```
 0
6/15/2009 11:35:55 PM
```On 16 Jun, 01:35, Junoexpress <MTBrenne...@gmail.com> wrote:
> On Jun 14, 6:23=A0am, Rune Allnor <all...@tele.ntnu.no> wrote:
>
>
>
> > On 14 Jun, 05:30, Junoexpress <MTBrenne...@gmail.com> wrote:
>
> > > On Jun 13, 4:00=A0pm, Rune Allnor <all...@tele.ntnu.no> wrote:> On 13=
Jun, 21:33, junoexpress <MTBrenne...@gmail.com> wrote:
>
> > > > > Hi,
>
> > > > > In the literature, there is a common claim made that the performa=
nce
> > > > > of MUSIC for direction of arrival estimation (DOA) is affected wh=
en
> > > > > the wrong number of directional sources is assumed. There is no
> > > > > argument presented to support this claim, nor any references give=
n,
> > > > > just the claim.
>
> > > > The claims may or may not be true, depending on exactly
> > > > how =A0they are phrased. Do you have any pointers to where
> > > > such claims are made?
>
> > > This claim is found in a good many papers on the topic of signal
> > > enumeration. Two that make the statement clearly are:
> > > 1) IEEE Trans Acc, Speech, and Signal Processing, vol. 38, no. 11,
> > > 1990
> > > "On Information Theoretic Criteria...." by Wong, Zhang, Reilly, and
> > > Yip
> > > (see text after eqn 5 in article)
> > > 2) IEEE Trans Signal Processing, vol. 39, no. 8, 1991
> > > "A Parametric Method for Determining the Number of Signals in Narrow-
> > > Band Direction Finding"
> > > by Wu and Fuhrman (see first paragraph)
>
> > > > There are several causes for inaccuracies in the MUSIC-type
> > > > estimators. One is the SNR, others are related to wrong order
> > > > estimates, like if there in reality are 4 signals present,
> > > > but the order estimator only finds 3 of them. In such cases,
> > > > it is likely that at least some of the DoAs are off, either
> > > > because the SNR is low or the 'missing' signal lies very close
> > > > to one of the others. If the 'missing' signal has a significantly
> > > > smaller amplitude than the others, the remaining DoA estimates
> > > > might be accurate anyway.
>
> > > Your line of reasoning is pretty much what makes me doubt this claim.
> > > A source that is missed, is most likely missed because its SNR is ver=
y
> > > small.
>
> > Not necesarily. There can be any number of reasons why a
> > source is missed. Small SNR is just one of them.
>
> > There is one aspect of order estimators you need to be
> > aware of: For AR models, order estimators are formally
> > are derived from statistical analyses of the reflection
> > coefficients that represent signal residuals during the
> > Levinson recursion.
>
> > MUSIC can not be represented as a Levinson recursion,
> > it's based on eigenvector decompositions. So the *formal*
> > statistical analysis, which works on the reflection
> > coefficients, don't work with the eigenvalues.
>
> > Now, this does *not* mean that oprder estimators do not
> > work with eigenvector decompositions - they do. It means
> > that one has bodged a tool to work in a context it was
> > not designed for. Which also goes a long way to explain
> > why order estimates might be off from time to time, with
> > no apparent reason.
>
> If you consider this from a math point of view, the basic fact is that
> the notion of a "signal subspace" and a "noise subspace" are fiction.
> point of view is not well understood, and probably should be
> investigated more.

No, there isn't. The terms are well-defined, the maths simple.
As long as one is comfortable with N-dimensional complex-valued
vector spaces. But those are just a matter of familiarization,
like i =3D sqrt(-1). A big hurdle for the newbie, second nature
to the somewhat more experienced.

> > > The components of the stronger sources on the evr that gets
> > > dropped from the signal subspace and gets put into the noise sub-spac=
e
> > > cannot be that large, so when you run say Spectral MUSIC,
>
> > Spectral MUSIC is...? If you are talking about the MUSIC
> > pseudo spectrum, keep in mind that there is no information
> > about the signal spectrum encoded in the pseudo spectrum.
>
> There are two basic types of MUSIC: "spectral" MUSIC (which is what
> was originally proposed by Schmidt) and "ROOT" MUSIC (which is a
> simple extension of spectral MUSIC that works a bit better).
> Estimates about the source AOAs can be made (if again we make a boat-
> load full of assumptions ;>)) from both.

MUSIC is Scmhidt's original method that in principle works
with arrays of any geometry. The Root MUSIC is an ad-hoc
adaption for the case of Uniform Linear Arrays. It might have
been an interesting alternative, were it not for other methods
that addressed the ULA directly, which turned out to be far
more computationally efficient.

> > > the location
> > > where the reciprocal of the projection of the steering vectors onto
> > > the noise subspace has its max value should not change appreciably.
>
> > Remember, you are working D-manifolds in an P-dimensional
> > complex-valued vector space. Don't expect your intuition
> > to be of the best help...
>
> > > > No easy answers.
>
> > > > > Does this reasoning sound like the justification for the claim ab=
out
> > > > > MUSIC I presented, or is there something else I am missing?
>
> > > > Yes, there is.
>
> > > > MUSIC-type estimators (meaning all estimators which
> > > > implicitly or explicitly use a covariance matrix of
> > > > order P to estimate the parameters of D signals) *fail*
> > > > *unconditionally* when D >=3DP.
>
> > > The noise in the system (i.e. AWGN in the channels) will guarantee
> > > that the covariance matrix has full rank. This condition is certainly
> > > satisfied in all of the professional treatments of MUSIC you see in
> > > the lit.
>
> > You need to think one step further: The basis for the
> > noise subspace needs to be of rank at least 1 for MUSIC
> > and friends to work. Once you have a signal that contains
> > P (or P/2) or more sinusoidals, this no longer holds and
> > MUSIC fails unconditionally.
>
> > > I am assuming the are are less sources than antennas here.
>
> > You can certainly do that for academic purposes. That's
> > a very stupid thing to do in the real world.
>
> Not really. In many applications the cost of the array alone prohibits
> you from using a large array size and you have to make that
> assumption.

That's the blunder you and everybody else who try to use these
methods make: The fact that you assume that the sensor will
never see more than a small number of sources, does not
prevent that from happening.

So when (not if) the case of D >=3DP happens, the system breaks
down. Your clients are left in a void where nothing works, and
you don't understand why.

Before you try and make a living out of this (your lack
of historical knowledge and the statement above are
certain give-aways), take some time to think through the
legal obligations that are activated once you charge
be liable to damage compensations for any glitch or problem

failure, I will waste no time in suggest you might be
guilty of professional misconduct or fraud, if I find
you used MUSIC and only assumed (as opposed to ensured)
that the D < P.

> > > And there are other problems of course that could arise (such as the
> > > presence of correlated sources, or an array whose antenna spacings ar=
e
> > > greater than half a wavelength, or signals which are wide-band, etc
> > > which will also act to screw up MUSIC),
>
> > Most of those can be handled. Tedious, but not very
> > difficult.
>
> > > but neither I, nor the
> > > articles to which I am referring, assume any of these conditions hold=
..
>
> > > > If you want to, repeat the excercise with various SNRs,
> > > > and with different MUSIC implementations.
>
> > > Been there, done that.
>
> > > > Rune
>
> > > Thanks for your input Rune. It seems that you're the only person who
> > > responds to array signal processing questions. I kinda thought there
> > > would be some people on the group who could understand this stuff.
>
> > I am sure there are.
>
> > > Maybe few professionals post here or are in another group.
>
> > yourself: they just don't want to learn about the
> > pathological shortfalls of these types of methods.
>
> Unfortunately, there are people on both sides of the fence who are
> biased and insecure, which really does make it difficult for the two
> sides to communicate in a meaningful and respectful manner.

There isn't. The only problem is that most people don't
know the excercise I pointed out for you earlier on.
If everybody did, everybody would agree with me.

> But I'm
> sure neither of us wants to contribute to such counter-productive
> exchanges. I know that I don't. Personally I find the real-life
> problems you' re talking about exciting and I do think they have to be
> addressed to get a real understanding of how things work.

Not what MUSIC is concerned. Just run the excercise I showed
you, and contemplate what would happen if a similar situation
occured after you installed and accepted payment for one of

> > The 'professionals' - people who work for DSP for a living
> > in the real world - just don't use MUSIC. For the very
> > reasons I've done my best to point out for you. If you don't
> > believe me, just look around for yourself and try and find
> > out how many real-world applications actually use these
> > sorts of methods.
>
> > There aren't too many - I'm not aware of a single one.
>
> > Rune
>
> Good to hear: that's what keeps me in business. ;>)

If you say so. Just make sure you are well insured against
claims of professional misconduct, if you decide to sell
these kinds of things.

Rune
```
 0
allnor (8509)
6/16/2009 8:32:35 AM
```On Jun 16, 4:32=A0am, Rune Allnor <all...@tele.ntnu.no> wrote:
> On 16 Jun, 01:35, Junoexpress <MTBrenne...@gmail.com> wrote:
>
>
>
> > On Jun 14, 6:23=A0am, Rune Allnor <all...@tele.ntnu.no> wrote:
>
> > > On 14 Jun, 05:30, Junoexpress <MTBrenne...@gmail.com> wrote:
>
> > > > On Jun 13, 4:00=A0pm, Rune Allnor <all...@tele.ntnu.no> wrote:> On =
13 Jun, 21:33, junoexpress <MTBrenne...@gmail.com> wrote:
>
> > > > > > Hi,
>
> > > > > > In the literature, there is a common claim made that the perfor=
mance
> > > > > > of MUSIC for direction of arrival estimation (DOA) is affected =
when
> > > > > > the wrong number of directional sources is assumed. There is no
> > > > > > argument presented to support this claim, nor any references gi=
ven,
> > > > > > just the claim.
>
> > > > > The claims may or may not be true, depending on exactly
> > > > > how =A0they are phrased. Do you have any pointers to where
> > > > > such claims are made?
>
> > > > This claim is found in a good many papers on the topic of signal
> > > > enumeration. Two that make the statement clearly are:
> > > > 1) IEEE Trans Acc, Speech, and Signal Processing, vol. 38, no. 11,
> > > > 1990
> > > > "On Information Theoretic Criteria...." by Wong, Zhang, Reilly, and
> > > > Yip
> > > > (see text after eqn 5 in article)
> > > > 2) IEEE Trans Signal Processing, vol. 39, no. 8, 1991
> > > > "A Parametric Method for Determining the Number of Signals in Narro=
w-
> > > > Band Direction Finding"
> > > > by Wu and Fuhrman (see first paragraph)
>
> > > > > There are several causes for inaccuracies in the MUSIC-type
> > > > > estimators. One is the SNR, others are related to wrong order
> > > > > estimates, like if there in reality are 4 signals present,
> > > > > but the order estimator only finds 3 of them. In such cases,
> > > > > it is likely that at least some of the DoAs are off, either
> > > > > because the SNR is low or the 'missing' signal lies very close
> > > > > to one of the others. If the 'missing' signal has a significantly
> > > > > smaller amplitude than the others, the remaining DoA estimates
> > > > > might be accurate anyway.
>
> > > > Your line of reasoning is pretty much what makes me doubt this clai=
m.
> > > > A source that is missed, is most likely missed because its SNR is v=
ery
> > > > small.
>
> > > Not necesarily. There can be any number of reasons why a
> > > source is missed. Small SNR is just one of them.
>
> > > There is one aspect of order estimators you need to be
> > > aware of: For AR models, order estimators are formally
> > > are derived from statistical analyses of the reflection
> > > coefficients that represent signal residuals during the
> > > Levinson recursion.
>
> > > MUSIC can not be represented as a Levinson recursion,
> > > it's based on eigenvector decompositions. So the *formal*
> > > statistical analysis, which works on the reflection
> > > coefficients, don't work with the eigenvalues.
>
> > > Now, this does *not* mean that oprder estimators do not
> > > work with eigenvector decompositions - they do. It means
> > > that one has bodged a tool to work in a context it was
> > > not designed for. Which also goes a long way to explain
> > > why order estimates might be off from time to time, with
> > > no apparent reason.
>
> > If you consider this from a math point of view, the basic fact is that
> > the notion of a "signal subspace" and a "noise subspace" are fiction.
> > point of view is not well understood, and probably should be
> > investigated more.
>
> No, there isn't. The terms are well-defined, the maths simple.
> As long as one is comfortable with N-dimensional complex-valued
> vector spaces. But those are just a matter of familiarization,
> like i =3D sqrt(-1). A big hurdle for the newbie, second nature
> to the somewhat more experienced.
>
I doubt it. I'm a PhD in math and I know from my experience that there
is a fair amount of algebraic geometry involved in understanding array
manifolds. I've corrected the errors of many engineers who don't
understand what a complex Steifel manifolds (or even a manifold for
that matter), let alone its topology, so I know this from experience
to be the case.

> > > > The components of the stronger sources on the evr that gets
> > > > dropped from the signal subspace and gets put into the noise sub-sp=
ace
> > > > cannot be that large, so when you run say Spectral MUSIC,
>
> > > Spectral MUSIC is...? If you are talking about the MUSIC
> > > pseudo spectrum, keep in mind that there is no information
> > > about the signal spectrum encoded in the pseudo spectrum.
>
> > There are two basic types of MUSIC: "spectral" MUSIC (which is what
> > was originally proposed by Schmidt) and "ROOT" MUSIC (which is a
> > simple extension of spectral MUSIC that works a bit better).
> > Estimates about the source AOAs can be made (if again we make a boat-
> > load full of assumptions ;>)) from both.
>
> MUSIC is Scmhidt's original method that in principle works
> with arrays of any geometry. The Root MUSIC is an ad-hoc
> adaption for the case of Uniform Linear Arrays. It might have
> been an interesting alternative, were it not for other methods
> that addressed the ULA directly, which turned out to be far
> more computationally efficient.
>
>
>
> > > > the location
> > > > where the reciprocal of the projection of the steering vectors onto
> > > > the noise subspace has its max value should not change appreciably.
>
> > > Remember, you are working D-manifolds in an P-dimensional
> > > complex-valued vector space. Don't expect your intuition
> > > to be of the best help...
>
> > > > > No easy answers.
>
> > > > > > Does this reasoning sound like the justification for the claim =
> > > > > > MUSIC I presented, or is there something else I am missing?
>
> > > > > Yes, there is.
>
> > > > > MUSIC-type estimators (meaning all estimators which
> > > > > implicitly or explicitly use a covariance matrix of
> > > > > order P to estimate the parameters of D signals) *fail*
> > > > > *unconditionally* when D >=3DP.
>
> > > > The noise in the system (i.e. AWGN in the channels) will guarantee
> > > > that the covariance matrix has full rank. This condition is certain=
ly
> > > > satisfied in all of the professional treatments of MUSIC you see in
> > > > the lit.
>
> > > You need to think one step further: The basis for the
> > > noise subspace needs to be of rank at least 1 for MUSIC
> > > and friends to work. Once you have a signal that contains
> > > P (or P/2) or more sinusoidals, this no longer holds and
> > > MUSIC fails unconditionally.
>
> > > > I am assuming the are are less sources than antennas here.
>
> > > You can certainly do that for academic purposes. That's
> > > a very stupid thing to do in the real world.
>
> > Not really. In many applications the cost of the array alone prohibits
> > you from using a large array size and you have to make that
> > assumption.
>
> That's the blunder you and everybody else who try to use these
> methods make: The fact that you assume that the sensor will
> never see more than a small number of sources, does not
> prevent that from happening.
>
> So when (not if) the case of D >=3DP happens, the system breaks
> down. Your clients are left in a void where nothing works, and
> you don't understand why.
>
> Before you try and make a living out of this (your lack
> of historical knowledge and the statement above are
> certain give-aways), take some time to think through the
> legal obligations that are activated once you charge
> be liable to damage compensations for any glitch or problem
>
> If your clients hire me to review your system after a
> failure, I will waste no time in suggest you might be
> guilty of professional misconduct or fraud, if I find
> you used MUSIC and only assumed (as opposed to ensured)
> that the D < P.
>
You have to be very clear what the limitations of your method are. I
don't know your background, but I don't know any professionals who
don't spell these type of things out up front.
>
>
> > > > And there are other problems of course that could arise (such as th=
e
> > > > presence of correlated sources, or an array whose antenna spacings =
are
> > > > greater than half a wavelength, or signals which are wide-band, etc
> > > > which will also act to screw up MUSIC),
>
> > > Most of those can be handled. Tedious, but not very
> > > difficult.
>
> > > > but neither I, nor the
> > > > articles to which I am referring, assume any of these conditions ho=
ld.
>
> > > > > If you want to, repeat the excercise with various SNRs,
> > > > > and with different MUSIC implementations.
>
> > > > Been there, done that.
>
> > > > > Rune
>
> > > > Thanks for your input Rune. It seems that you're the only person wh=
o
> > > > responds to array signal processing questions. I kinda thought ther=
e
> > > > would be some people on the group who could understand this stuff.
>
> > > I am sure there are.
>
> > > > Maybe few professionals post here or are in another group.
>
> > > yourself: they just don't want to learn about the
> > > pathological shortfalls of these types of methods.
>
> > Unfortunately, there are people on both sides of the fence who are
> > biased and insecure, which really does make it difficult for the two
> > sides to communicate in a meaningful and respectful manner.
>
> There isn't. The only problem is that most people don't
> know the excercise I pointed out for you earlier on.
> If everybody did, everybody would agree with me.
>
> > But I'm
> > sure neither of us wants to contribute to such counter-productive
> > exchanges. I know that I don't. Personally I find the real-life
> > problems you' re talking about exciting and I do think they have to be
> > addressed to get a real understanding of how things work.
>
> Not what MUSIC is concerned. Just run the excercise I showed
> you, and contemplate what would happen if a similar situation
> occured after you installed and accepted payment for one of
>
> > > The 'professionals' - people who work for DSP for a living
> > > in the real world - just don't use MUSIC. For the very
> > > reasons I've done my best to point out for you. If you don't
> > > believe me, just look around for yourself and try and find
> > > out how many real-world applications actually use these
> > > sorts of methods.
>
> > > There aren't too many - I'm not aware of a single one.
>
> > > Rune
>
> > Good to hear: that's what keeps me in business. ;>)
>
> If you say so. Just make sure you are well insured against
> claims of professional misconduct, if you decide to sell
> these kinds of things.
>
> Rune

I do math, not engineering. All of my equations have worked so far,
and consulting has never been better. ;>)

M

```
 0
6/16/2009 8:22:41 PM
```On 16 Jun, 22:22, Junoexpress <MTBrenne...@gmail.com> wrote:
> On Jun 16, 4:32=A0am, Rune Allnor <all...@tele.ntnu.no> wrote:

> > > If you consider this from a math point of view, the basic fact is tha=
t
> > > the notion of a "signal subspace" and a "noise subspace" are fiction.
> > > point of view is not well understood, and probably should be
> > > investigated more.
>
> > No, there isn't. The terms are well-defined, the maths simple.
> > As long as one is comfortable with N-dimensional complex-valued
> > vector spaces. But those are just a matter of familiarization,
> > like i =3D sqrt(-1). A big hurdle for the newbie, second nature
> > to the somewhat more experienced.
>
> I doubt it. I'm a PhD in math and I know from my experience that there
> is a fair amount of algebraic geometry involved in understanding array
> manifolds. I've corrected the errors of many engineers who don't
> understand what a complex Steifel manifolds (or even a manifold for
> that matter), let alone its topology, so I know this from experience
> to be the case.

Still, you don't undrestand the trivial basics of vector spaces.

> > If your clients hire me to review your system after a
> > failure, I will waste no time in suggest you might be
> > guilty of professional misconduct or fraud, if I find
> > you used MUSIC and only assumed (as opposed to ensured)
> > that the D < P.
>
> You have to be very clear what the limitations of your method are. I
> don't know your background, but I don't know any professionals who
> don't spell these type of things out up front.

You claim to be a professional. You actively disregard
precise and clear warnings about trivial pathologies
of the method you claim to build a business on.

That's gross professional misconduct at the best of times,
and pretty close to fraud.

Rune
```
 0
allnor (8509)
6/16/2009 8:44:22 PM
```On Jun 15, 4:35 pm, Junoexpress <MTBrenne...@gmail.com> wrote:
> On Jun 14, 6:23 am, Rune Allnor <all...@tele.ntnu.no> wrote:
....
> > ...    If you don't
> > believe me, just look around for yourself and try and find
> > out how many real-world applications actually use these
> > sorts of methods.
>
> > There aren't too many - I'm not aware of a single one.
>
> > Rune
>
> Good to hear: that's what keeps me in business. ;>)
>
> M

Are there any such systems that have been tested in use by the actual
practitioners and remained in use after test? Or are you saying that

Dale B. Dalrymple
```
 0
dbd1 (1036)
6/16/2009 9:49:49 PM
```On Jun 16, 4:44=A0pm, Rune Allnor <all...@tele.ntnu.no> wrote:
> On 16 Jun, 22:22, Junoexpress <MTBrenne...@gmail.com> wrote:
>
>
>
> > On Jun 16, 4:32=A0am, Rune Allnor <all...@tele.ntnu.no> wrote:
> > > > If you consider this from a math point of view, the basic fact is t=
hat
> > > > the notion of a "signal subspace" and a "noise subspace" are fictio=
n.
> > > > point of view is not well understood, and probably should be
> > > > investigated more.
>
> > > No, there isn't. The terms are well-defined, the maths simple.
> > > As long as one is comfortable with N-dimensional complex-valued
> > > vector spaces. But those are just a matter of familiarization,
> > > like i =3D sqrt(-1). A big hurdle for the newbie, second nature
> > > to the somewhat more experienced.
>
> > I doubt it. I'm a PhD in math and I know from my experience that there
> > is a fair amount of algebraic geometry involved in understanding array
> > manifolds. I've corrected the errors of many engineers who don't
> > understand what a complex Steifel manifolds (or even a manifold for
> > that matter), let alone its topology, so I know this from experience
> > to be the case.
>
> Still, you don't undrestand the trivial basics of vector spaces.
>
> > > If your clients hire me to review your system after a
> > > failure, I will waste no time in suggest you might be
> > > guilty of professional misconduct or fraud, if I find
> > > you used MUSIC and only assumed (as opposed to ensured)
> > > that the D < P.
>
> > You have to be very clear what the limitations of your method are. I
> > don't know your background, but I don't know any professionals who
> > don't spell these type of things out up front.
>
> You claim to be a professional. You actively disregard
> precise and clear warnings about trivial pathologies
> of the method you claim to build a business on.
>
> That's gross professional misconduct at the best of times,
> and pretty close to fraud.
>
> Rune

I've made no "claims", as my standard disclaimer clearly shows:

STANDARD DISCLAIMER

This product is meant for educational purposes only. Any resemblance
to real persons, living or dead is purely coincidental. This is work
in progress and subject to change. Void where prohibited. Some
assembly required. List each check separately by bank number.
Batteries not included. Contents may settle during shipment. Use only
as directed. COUNT YOUR CHANGE. No other warranty expressed or
implied. Do not use while operating a motor vehicle or heavy
equipment. Postage will be paid by addressee. Subject to regulatory
approval. This is not an offer to sell securities.

Apply only to affected area. May be too intense for some viewers. Do
not stamp. Use other side for additional listings. For recreational
use only. Do not disturb. All models over 18 years of age.

Not recommended for children. Prerecorded for this time zone.
Reproduction strictly prohibited. No solicitors. Shake well before
using. No user-serviceable parts inside. For external use only. If
condition worsens, discontinue use and consult a physician.

Freshest if eaten before date on carton. Subject to change without
notice. Times approximate. No substitutions. Simulated picture. Use
for the prevention of disease only. No postage necessary if mailed in
the United States. Please remain seated until the ride has come to a
complete stop. Breaking seal constitutes acceptance of agreement.

For off-road use only. As seen on TV. One size fits all. Many
suitcases look alike. Contains a substantial amount of non-tobacco
ingredients. Colors may, in time, fade. We have sent the forms which
seem right for you. Slippery when wet. For office use only. Not
affiliated with the American Red Cross. Drop in any mailbox. Edited
for television. Keep cool; process promptly. No breakfast after 10 am.
Post office will not deliver without postage. List was current at time
of printing. Return to sender, no forwarding order on file, unable to
forward. Not responsible for direct, indirect, incidental, or
consequential damages resulting from any defect, error, or failure to
perform.

At participating locations only. Not the Beatles. Penalty for private
use. See label for sequence. Substantial penalty for early withdrawal.
Do not write below this line. Falling rock. Lost ticket pays maximum
here. Avoid contact with skin. Sanitized for your protection. Be sure
each item is properly endorsed. Sign here without admitting guilt.
Slightly higher west of the Mississippi. Employees and their families
are not eligible. Beware of dog.

Contestants have been briefed on some questions before the show. You
must be present to win. No passes accepted for this engagement. No
purchase necessary. Some restrictions apply. Limited time offer, call
now to ensure prompt delivery. Celebrity voices impersonated.
Processed at location stamped in code at top of carton. Shading within
a garment may occur. Use only in a well-ventilated area. Keep away
from fire or flames. Replace with same type. Approved for veterans.
Keep out of reach of children. Booths for two or more. Check here if
tax deductible. Some equipment shown is optional.

Price does not include taxes. No Canadian coins. No alcohol, dogs, or
horses. No anchovies unless otherwise specified. Restaurant package,
not for resale. List at least two alternate dates. First pull up, then
pull down. Call toll free number before digging. Take only as
directed. Driver does not carry cash. Some of the trademarks mentioned
in this product appear for identification purposes only. Objects in
mirror may be closer than they appear.

Record additional transactions on back of previous stub. Unix is a
registered trademark of AT&T. Do not fold, spindle, or mutilate. No
transfers issued until the bus comes to a complete stop. Package sold
by weight, not volume. This page left intentionally blank. I just work

These materials have been prepared for informational purposes only and
are not legal advice. Transmission of the information is not intended
to create, and receipt does not constitute, an attorney-client
relationship. Internet subscribers and online readers should not act
upon this information without seeking professional counsel. Use at

after dark. Additional charges may apply.

Customer voluntarily assumes all risks, known and unknown, of any
injury, however caused, even if caused in whole or in part by the
action, inaction, or negligence of any party, to the full extent
allowed by California law.

This supersedes all previous notices.

The information contained in this transmission is attorney privileged
and/or confidential information intended for the use of the individual
or entity named above. If the reader of this message is not the
intended recipient, you are hereby notified that any dissemination,
distribution or copying of this communication is strictly prohibited.
"

OK Rune, it's been a whole lotta fun, but I've had enough cloak and
dagger bullshit for a while.

Best Regards,

M
```
 0
6/16/2009 10:35:24 PM
```On Jun 16, 5:49=A0pm, dbd <d...@ieee.org> wrote:
> On Jun 15, 4:35 pm, Junoexpress <MTBrenne...@gmail.com> wrote:
>
> > On Jun 14, 6:23 am, Rune Allnor <all...@tele.ntnu.no> wrote:
> ...
> > > ... =A0 =A0If you don't
> > > believe me, just look around for yourself and try and find
> > > out how many real-world applications actually use these
> > > sorts of methods.
>
> > > There aren't too many - I'm not aware of a single one.
>
> > > Rune
>
> > Good to hear: that's what keeps me in business. ;>)
>
> > M
>
> Are there any such systems that have been tested in use by the actual
> practitioners and remained in use after test? Or are you saying that
>
> Dale B. Dalrymple

I don't do "systems" (which is why I am so amused by this thread). I
solve math problems that scientists and engineers can't solve.

Some of my work has been the basis for entire new fields, some of it
has remained a curiosity. But to tell the truth, I could care less
either way and I've enjoyed doing both equally well. I do what I do,
because I enjoy it, and I enjoy the challenge.

Regards,

Matt

Matt
```
 0
6/17/2009 12:27:16 AM
```On Jun 16, 5:27 pm, Junoexpress <MTBrenne...@gmail.com> wrote:
> On Jun 16, 5:49 pm, dbd <d...@ieee.org> wrote:
>
>
>
> > On Jun 15, 4:35 pm, Junoexpress <MTBrenne...@gmail.com> wrote:
>
> > > On Jun 14, 6:23 am, Rune Allnor <all...@tele.ntnu.no> wrote:
> > ...
> > > > ...    If you don't
> > > > believe me, just look around for yourself and try and find
> > > > out how many real-world applications actually use these
> > > > sorts of methods.
>
> > > > There aren't too many - I'm not aware of a single one.
>
> > > > Rune
>
> > > Good to hear: that's what keeps me in business. ;>)
>
> > > M
>
> > Are there any such systems that have been tested in use by the actual
> > practitioners and remained in use after test? Or are you saying that
> > it is your business to protect practitioners from such systems?
>
> > Dale B. Dalrymple
>
> I don't do "systems" (which is why I am so amused by this thread). I
> solve math problems that scientists and engineers can't solve.
>
> Some of my work has been the basis for entire new fields, some of it
> has remained a curiosity. But to tell the truth, I could care less
> either way and I've enjoyed doing both equally well. I do what I do,
> because I enjoy it, and I enjoy the challenge.
>
> Regards,
>
> Matt
>
> Matt

Ok, so you are a mathematician without applications experience.

Dale B. Dalrymple
```
 0
dbd1 (1036)
6/17/2009 1:33:41 AM
```On Jun 16, 9:33=A0pm, dbd <d...@ieee.org> wrote:
> On Jun 16, 5:27 pm, Junoexpress <MTBrenne...@gmail.com> wrote:
>
> Ok, so you are a mathematician without applications experience.
>
> Dale B. Dalrymple

I develop the theory you apply.   ;>)
```
 0
6/17/2009 5:56:00 AM
```On 17 Jun, 07:56, Junoexpress <MTBrenne...@gmail.com> wrote:
> On Jun 16, 9:33=A0pm, dbd <d...@ieee.org> wrote:
>
> > On Jun 16, 5:27 pm, Junoexpress <MTBrenne...@gmail.com> wrote:
>
> > Ok, so you are a mathematician without applications experience.
>
> > Dale B. Dalrymple
>
> I develop the theory you apply. =A0 ;>)

You might think so, but the fact of the matter is that
you don't understand the theory that has been standard
in the DSP community for 35 years (It is common to trace
MUSIC-type methods to Pisarenko's 1973 paper.)

Not only have this theory been around for decades, it is
so simple that it can be explained to a reasonably bright
12-year-old without much difficulty, using only a piece
of paper and a couple of sticks.

Rune
```
 0
allnor (8509)
6/17/2009 7:42:33 AM
```On 17 Jun, 00:35, Junoexpress <MTBrenne...@gmail.com> wrote:
> On Jun 16, 4:44=A0pm, Rune Allnor <all...@tele.ntnu.no> wrote:
>
>
>
>
>
> > On 16 Jun, 22:22, Junoexpress <MTBrenne...@gmail.com> wrote:
>
> > > On Jun 16, 4:32=A0am, Rune Allnor <all...@tele.ntnu.no> wrote:
> > > > > If you consider this from a math point of view, the basic fact is=
that
> > > > > the notion of a "signal subspace" and a "noise subspace" are fict=
ion.
> > > > > There is a lot about this simple picture that from a mathematical
> > > > > point of view is not well understood, and probably should be
> > > > > investigated more.
>
> > > > No, there isn't. The terms are well-defined, the maths simple.
> > > > As long as one is comfortable with N-dimensional complex-valued
> > > > vector spaces. But those are just a matter of familiarization,
> > > > like i =3D sqrt(-1). A big hurdle for the newbie, second nature
> > > > to the somewhat more experienced.
>
> > > I doubt it. I'm a PhD in math and I know from my experience that ther=
e
> > > is a fair amount of algebraic geometry involved in understanding arra=
y
> > > manifolds. I've corrected the errors of many engineers who don't
> > > understand what a complex Steifel manifolds (or even a manifold for
> > > that matter), let alone its topology, so I know this from experience
> > > to be the case.
>
> > Still, you don't undrestand the trivial basics of vector spaces.
>
> > > > If your clients hire me to review your system after a
> > > > failure, I will waste no time in suggest you might be
> > > > guilty of professional misconduct or fraud, if I find
> > > > you used MUSIC and only assumed (as opposed to ensured)
> > > > that the D < P.
>
> > > You have to be very clear what the limitations of your method are. I
> > > don't know your background, but I don't know any professionals who
> > > don't spell these type of things out up front.
>
> > You claim to be a professional. You actively disregard
> > precise and clear warnings about trivial pathologies
> > of the method you claim to build a business on.
>
> > That's gross professional misconduct at the best of times,
> > and pretty close to fraud.
>
> > Rune
>
> I've made no "claims", as my standard disclaimer clearly shows:
>
> STANDARD DISCLAIMER

You might want to be very careful about how you

Legal details probably differ from location to
location, but at least in my neck of the woods,
you approach 'fraud' in the legal sense when

1) Money change hands.
2) There is a certain discrepancy between what
the user/buyer *thinks* he gets and what he
*actually* gets.

There are also quite strict damage compensation
clauses, where the manufacturer (or a representative,
such as importer or retail outlet) of a product is
held legally responsible for damages that are caused
by the product.

Do note that this has nothing to do with unsafe or
uncorrect use of a product: The manufacurer or his
representative is held responsible for damages, no
matter what.

A disclaimer doesn't change any of this, as local
banks are in the process of finding out.

Over the past few years they sold 'financial products'
to customers, where the customers took up loans, at some
interest rate, and placed the money in the market, at
some other interst rate. Details in the press are a bit
vague as to exactly what was sold, but problems arose
when interest rates on the loans exceeded profits from
the market. Lots of people lost hundreds of thousands
of dollars on this, and sued the banks.

There are several legal processes at work over these
questions right now, so the end result remains to be
seen.

However, you might want to note that

- The banks issue standard disclaimers no matter what
product they sell their customers
- The product in question was based on the *assumption*
that the financial market would not collapse
- The courts hold product brokers responsible for
informing the users 'sufficiently well' about the
products, their benefits, and particularly the
risks.

Again, the Norwegian legal system probably differs in
the details from systems in other coutries. The main
principles should be the same, throughout the western
world.

Rune
```
 0
allnor (8509)
6/17/2009 8:05:50 AM

Similar Artilces:

Problem in MUSIC Algorithm for DOA Estimation
Hi all......... I want to find out angle of arrival using planer antenna array for radar (Digital Monopulse) application. For concept development, first i make 2x2 planer array, and try to find out direction of arrival of sources, further i need to make null at the direction of interference. which algorithm is better for that???? or MUSIC algorithm is suitable for that???? I try to use MUSIC algorithm for DOA application, and write codes in MATLAB for 1D MUSIC. these codes gives DOA, but have some problem; (i take linear array of 10 elements, f = 1GHz and sampling frequency Fs = 5GHz) 1) the resolution is not as good as written in literature. 2) if i take no of signal > 2 then it able to find out DOA but Estimation of no. of signal is only 2 (it gives M - H (no of multiplicity of minimun eigen values) is only 1 or 2 for all the cases). I think some problem in signal(X(t)=AS + N), which i take as; Xn = Sin (wt + k d Sin(thetha))* exp (-j*(n-1)k d Sin(thetha)) Matlab codes for that is given below; for k=1:samples % no of time instants for i=1:M % no of elements for ns=1:D % no of incoming signals S1(i,k)=S1(i,k)+ sin(2*pi*f*k/Fs + 2*pi*sin(theta(ns))/dfactor)* exp(-j*(i-1)*2*pi*sin(theta(ns))/dfactor); end end end X = awgn(S1,20); % Add white Gaussian noise to signal (M x sampless) can any one give ur valuable suggations. THANKS. On 18 Sep, 14:55, "amit00" <getamitshu...@rediffmail.com...

DOA Estimation
Hi all, I am working in Array Signal Processing. In that i need DOA estimation. So if any one had Matlab code for DOA Estimation or any one can tell how to fine DOA, it would be great help So please help me Thanks in advance chowdary, chowdarydv@yahoo.com (Chowdary) wrote in message news:<bbcefd36.0404211904.69bdc056@posting.google.com>... > Hi all, > I am working in Array Signal Processing. In that i need DOA > estimation. So if any one had Matlab code for DOA Estimation or any > one can tell how to fine DOA, it would be great help > So please help me Check out ...

Music Genres and DSP
Hi! I am currently investigating DSP techniques for my final-year university project. I want to create a program that uses an artificial neural network in order to classify music genres. Unfortunately, I have no prior experience with DSP. I was wondering if anyone here could point me in the right direction. I am particularly interested in DSP techniques that can be used to extract features of music which are "informative" in terms of genre classification. The only thing I can think of is BPM and dominant frequency extraction. Any help, comments or links for further reading would be greatly appreciated. Thank you! BigMomma wrote: > I am particularly interested in DSP techniques that can be used > to extract features of music which are "informative" in terms of > genre classification. Here's some conferences whose online proceedings will provide entry points and further references. http://smcnetwork.org/conferences http://www.google.com/search?num=50&q=dafx+proceedings Martin -- Quidquid latine scriptum est, altum videtur. ...

DOA estimation #2
i have implemented MUSIC and ESPRIT algorithm using Matlab.i want to know what are the variations or modifications that can be done to these algorithms.i have studied effect of varying SNR,antenna elements,angular separation on these algorithms.but something more is required. On 27 Nov, 14:29, preetigup...@gmail.com wrote: > i have implemented MUSIC and ESPRIT algorithm using Matlab.i want to > know what are the variations or modifications =A0that can be done to > these algorithms.i have studied effect of varying SNR,antenna > elements,angular separation on these algorithms.but something more is > required. With ESPRIT you can check the Least Means Square method against the Total Least Squares method. With MUSIC you can check e.g. Classical MUSIC agains Root MUSIC (I remember having read somewhere about a Pop MUSIC variation too...) The most interesting tests are with model mis-match scenarios. Both these methods are designed with a non-damped unscaled expunential signal in mind. Try them with either a damping term or a scale term and see how well they perform. Then try and increase the number of signals. At some point, near N/2 where N is the number of elements in the array, you might notice some changes in the behaviour of the methods. Rune >On 27 Nov, 14:29, preetigup...@gmail.com wrote: >> i have implemented MUSIC and ESPRIT algorithm using Matlab.i want to >> know what are the variations or modifications =A0that can be done to >>...

DOA by MUSIC algorithm
HI everyone, I am going to do a project on implementation of DOA estimation algorithm using MUSIC. I have read the literature about MUSIC and about DOA estimation. Still I am not able to conceive the idea practically. The input signal to the array of antennas (say M antennas) is X. (consider a single snap shot) which is equal to X = (a(theta) * S) + n Then we need to find the eigen value of the autocorrelation matrix of X. There will be M eigen values and M eigen vectors correspondingly. If the number of directions is D (D < M), then the eigen vectors from D+1 to M represent the noise subsspace. So the MUSIC spectrum is given by P(theta) = 1 / (summation from D+1 to M (a(theta) * eigen vectors))^2 This is what I understand from the theoretical stuff I read. Am i right? If I write a program in MATLAB using the above logic, will it be right? Where else can I find some practical examples of MATLAB implementation? Any help will be of great use to me. Thank you. On 16 Aug, 00:45, "krish_dsp" <nmkr...@gmail.com> wrote: > HI everyone, > I am going to do a project on implementation of DOA estimation algorithm > using MUSIC. I have read the literature about MUSIC and about DOA > estimation. > Still I am not able to conceive the idea practically. The input signal to > the array of antennas (say M antennas) is X. (consider a single snap shot) > which is equal to > X = (a(theta) * S) + n I suppose S is the steering vector and a(theta) i...

DOA by using MUSIC
Hi all, I have already made some measurements on a basis of Planar array, the size of array is 100*100, The question is how to use some high resolution algorithm to get the angle of arrival such as azimuth and elevation angle, I know MUSIC can do, but I don't how? thanks in advance. David ...

Real Time DOA Estimation
Hi all, I am just wondering how one can estimate DOA in real time. what kind of data we can get in real time for estimating the DOA. If any one have that kind of data for estimating the DOA and if u like to share please send me and also give some hints how to estimate DOA. Thanks chowdary, chowdarydv@yahoo.com (Chowdary) wrote in message news:<bbcefd36.0407221142.3e1c5201@posting.google.com>... > Hi all, > > I am just wondering how one can estimate DOA in real time. what > kind of data we can get in real time for estimating the DOA. If any > one have that kind o...

OT: Music and DSP Engineer
Playing music and designing DSP SW Are these two things compatible ? strict SW logic and 'unlogical' art People from svensk Clavia, any answers ? Kind nordic regards, Yuri ytregubov@yahoo.com wrote: > Playing music and designing DSP SW > > Are these two things compatible ? > > strict SW logic and 'unlogical' art > > People from svensk Clavia, any answers ? Of course. There are many who do both. Some DSP software designers also swim and drive cars. Most enjoy sex. Jerry -- Engineering is the art of making what you want from things you can get. &...

MATLAB code for DOA Estimation
Hi, Am new to MATLAB. Does anyone have sample code for Direction of Arrival Estimation using the Delay and Sum Beamformer? Shane ...

Number of sources in DOA estimation
Hi everyone, I have a question relating to direction-of-arrival (DOA) estimation for MIMO systems. When using an antenna array, would it be possible to estimate the DOA of more multipath sources than the number of antennas in the array? The DOA estimation algorithms used are those based on second-order statistics: subspace-based methods like MUSIC and maximum likelihood methods like SAGE. I would think that extracting more inputs (multipath sources) than outputs (responses of indivual antennas of the array) from a system seems doubtful. However, you can tell SAGE for example to extract a number of DOAs that is greater than the number of antenna sensors. I wonder if it would be reliable to do that? Thank you very much for your replies. Greetings, Emmeric On Dec 16, 10:31 am, Emmeric <emmeric.tan...@intec.ugent.be> wrote: > Hi everyone, > > I have a question relating to direction-of-arrival (DOA) estimation > for MIMO systems. When using an antenna array, would it be possible to > estimate the DOA of more multipath sources than the number of antennas > in the array? The DOA estimation algorithms used are those based on > second-order statistics: subspace-based methods like MUSIC and maximum > likelihood methods like SAGE. > > I would think that extracting more inputs (multipath sources) than > outputs (responses of indivual antennas of the array) from a system > seems doubtful. However, you can tell SAGE for example to extract a &g...

Mean Square Error in DOA Estimation
Hi all, I got strucked in calculating the Mean Square Error(MSE) in the DOA Estimation. Can any one explain me or if you have please send me the matlab code how to plot MSE for differnt SNR's and if you have any other matlab code to show the performance of DOA Estimation, Please Please send it to me. Thanks in advance Chow. chow wrote: > Hi all, > > I got strucked in calculating the Mean Square Error(MSE) in the DOA > Estimation. Can any one explain me or if you have please send me the > matlab code how to plot MSE for differnt SNR's and if you have any > other matlab code to show the performance of DOA Estimation Try to get hold of van Trees' "Detection, estimation and modulation" vol IV, Optimum Array Processing. There are lots of such plots in that book. Now, computing the MSE only works with simulated data. You need to know the true DoA, and then compare that to the estimated DoA. The comparision gives an error, and from there computing the MSE of different DoA estimators or SNRs is straight-forward. Rune Rune Allnor wrote: > chow wrote: > >>Hi all, >> >>I got strucked in calculating the Mean Square Error(MSE) in the DOA >>Estimation. Can any one explain me or if you have please send me the >>matlab code how to plot MSE for differnt SNR's and if you have any >>other matlab code to show the performance of DOA Estimation > > > Try to get hold of van Trees' "...

Time Delay between signals in DOA Estimation
Hi all, I am working on the problem of DOA estimation. I have two signals whose angle should be estimated. can any one tell me how to introduce time delay between the two signals. if any had matlab code for this that would be great. Thanks chowdary. chowdarydv@yahoo.com (Chowdary) wrote in message news:<bbcefd36.0406220925.7b797eaf@posting.google.com>... > Hi all, > > I am working on the problem of DOA estimation. I have two signals > whose angle should be estimated. can any one tell me how to introduce > time delay between the two signals. if any had matlab code f...

=dsp= Music entrophy and Image Watermarking
>>"lucy" <losemind@yahoo.com> wrote in message >>news:coo4it\$2s2\$1@news.Stanford.EDU... > >>>> After learning how to measure entropy of music... I can begin to measure >>>> entropy of texts, etc.. that's going to be fun! > >> On Thu, 2 Dec 2004 17:53:45 -0500, "Someonekicked" <someonekicked@comcast.net> wrote: >>is this some joke ?! The model of entropy that can be readily recognized: In music--how often can an informed listener infer the next note in a phrase; ie how many bits are needed to ...

Intro: Blog on DSP for Hindustani Music
http://chaelaa.wordpress.com On Thu, 5 Jul 2012 23:37:18 -0700 (PDT), Rohit <rohitagarwal33@rediffmail.com> wrote: >http://chaelaa.wordpress.com Hello Rohit, That web page contains the sentence: "As DSP engineers, we should be able to look at a graph of any given segment of audio and recognize its characteristics." Such a sentence certainly does invite meditation. [-Rick-] On Friday, July 6, 2012 12:07:18 PM UTC+5:30, Rohit wrote: > http://chaelaa.wordpress.com It's our first step towards building automated music analysis algorithms sp= ecially for Hindustani vocalists. The Hindustani school of Indian Classical= Music carries a rich tradition of direct guru to disciple based learning w= hich has resulted in very old traditions of vocal presentation being alive = still today. To start recognizing these nuances in the sound we are startin= g with a visual approach. On Jul 7, 12:41=A0am, Rick Lyons <R.Lyons@_BOGUS_ieee.org> wrote: > On Thu, 5 Jul 2012 23:37:18 -0700 (PDT), Rohit > > <rohitagarwa...@rediffmail.com> wrote: > >http://chaelaa.wordpress.com > > Hello Rohit, > =A0 =A0That web page contains the sentence: > > =A0 =A0"As DSP engineers, we should be able to > =A0 =A0 look at a graph of any given segment of > =A0 =A0 audio and recognize its characteristics." > > Such a sentence certainly does invite meditation. > >...

Range and DOA estimation of Broadband Nearfield Sources

Time estimation for first steps in DSP programming
Hello, Could somebody give me a rough estimation of time needed for experienced Windows/C++/Math programmer to start efficiently developing applications on a Digital Signal Processor platform (TMS320C6xxx, CodeComposer, DSK development board)? I know that it is very difficult to give some general estimation, so please feel free to share with me any comments, experiences or even wild guesses you have. Which possible problems should be concerned during this process? Thanks, Goran Obradovic gorano@t-online.de (Goran Obradovic) writes: > Hello, > > Could somebody give me a rough esti...

DoA using MUSIC and Uniform Circular Array
Hi All The problem that I am facing is as below: In a DoA estimation problem, the key point is to implement the steering vector. I have implemented MUSIC algorithm for ULA and it seems to work fine i.e. the performance becomes better with increase in SNR and resolution increases with increase in elements. Basically,in the case of ULA-MUSIC, we have to search for power in each azimuth angle's direction and select the one with maximum. And same for UCA-MUSIC, but now for a given elevation angle, we have to search for all azimuth angles. Is this correct? However, the problem tha...

Matrix Pencil for DOA estimation using Uniform Circular Arrays(UCA)
I want to estimate DOA using Matrix Pencil method. Here, I use UCA antenna with signal model as: A=exp(j*k*R*cos(theta-2*pi*m/N); m=0,...N-1; k=2*pi/lambda; R: Radius ; theta: angle of arrival. After finding eigenvalues of Matrix Pencil is z. Please help me calculate theta from z. Thanks all! P/s: If I use ULA antenna with signal model as: A=exp(j*k*d*m*cos(theta); m=0,...N-1; d is distance of two nearest elements. I can calculate theta=cos^-1 {Im(ln(z)) /kd}. ...

MUSIC
Is MUSIC algorithm interesting to estimate (amplitude and frequency) of sinusoids corrupted by noise? Others propositions are welcome. Thank you in advance... Moctar mmoctar wrote: > Is MUSIC algorithm interesting to estimate (amplitude and frequency) of > sinusoids corrupted by noise? > Others propositions are welcome. > Thank you in advance... > Moctar On Jun 15, 9:26=A0am, "mmoctar" <mmoc...@gmail.com> wrote: > Is MUSIC algorithm interesting to estimate (amplitude and frequency) of > sinusoids corrupted by noise? > Others propositions are welcome. > Thank you in advance... > Moctar Depends on the situation, but sure, MUSIC or ESPRIT or variations of them are interesting for line spectrum estimation or signals that are sums or exponentials. Julius On 15 Jun, 15:26, "mmoctar" <mmoc...@gmail.com> wrote: > Is MUSIC algorithm interesting to estimate (amplitude and frequency) of > sinusoids corrupted by noise? MUSIC was designed to be a frequency estimator, so it can be used to estimate frequencies. If you know what you are doing, you can use the frequency estimates to estimate the corresponding amplitudes; just be aware that there is lots of superstition and mythology surrounding MUSIC and some of the derived results. Whether MUSIC is 'interesting' for these types of tasks depend entirely on the context of the analysis. MUSIC has certain shortfalls, and requires certain conditions to be guarante...

Music
I'm engaging a musician to write the music for a animation presentation. Can anyone who has been through process shed some light on what to look out for and how to make sure everything runs smoothly. Terms of engagement and licensing issues are of particular interest. I'd prefer to maintain all licensing rights to the music as it will be a signature piece for the animation. Thanks for any help "BOXA" <dustbin@hotmail.com> wrote in message news:d2hdr1\$eg2\$1@sparta.btinternet.com... | I'm engaging a musician to write the music for a animation presentation...

music
Hello! Has anyone developed a system with Paradox to catalogue music, i.e. albums, c-casettes and CD�s? I�d like to exchange experiences. Fritz fritz.peronius@welho.com Hi Fritz: I wrote something a few years ago to catalogue my library, e.g. authors, titles, documents, etc, and have used it to store info on music scores and CDs (classical & renaissance stuff mostly). It was a kind of 'concept machine' for another corporate project which ended up abandoned in favour of web-based software. I still use the original database on my home machine, and always meant ...

Music
Hi all, I want to do following. In the background should play a midi file. That's not the problem but when the midi file is played another one should start automatically. During playing the first midi file the second should be downloaded and so on. What I don't know is when the midi file is played and when I should start the next midi file. Anybody can help? John John wrote: > Hi all, > > I want to do following. > In the background should play a midi file. That's not the problem but when > the midi file is played another one should start automatically. Du...

music
i'm looking at the g4 ibook. i plan on keeping my pc for emails, web and all that nonsense. but want to go mac for running music editing software. namely samplitude and reason. i'm thinking about getting the 60gig drive upgrade... and a gig of ram. now... i can't quite figure out tho.. if the ibook comes with a cd burner. i don't care too much about dvds. but i need to burn cd's. overall... i'm trying to find out if this computer... with these upgrades will do the trick to handle a decent amount of hard disk recording... and big music editing programs. ...

Music
How do I add music to my I photo sideshow In article <1181047108.131416.265890@p47g2000hsd.googlegroups.com>, toppygeorge@yahoo.com wrote: > How do I add music to my I photo sideshow Click on the Music button? -- Tom Stiller PGP fingerprint = 5108 DDB2 9761 EDE5 E7E3 7BDA 71ED 6496 99C0 C7CF In article <tomstiller-463C16.09131505062007@comcast.dca.giganews.com>, Tom Stiller <tomstiller@comcast.net> wrote: > In article <1181047108.131416.265890@p47g2000hsd.googlegroups.com>, > toppygeorge@yahoo.com wrote: > > > How do I add music to my I photo sideshow > > Click on the Music button? Before or after typing "add music" in the search box of the Help window? ...

Web resources about - MUSIC and DOA Estimation - comp.dsp

Estimation - Wikipedia, the free encyclopedia
... here. For the racehorse, see Estimate (horse) . For the card game, see Estimate (card game) . For the symbol, see Estimated sign . Estimation ...

→ Why are software development task estimations regularly off by a factor of 2-3?
Michael Wolfe: Let’s take a hike on the coast from San Francisco to Los Angeles to visit our friends in Newport Beach. Amazing.

Agile Estimation with the Bucket System
The “Bucket System” is a way to do estimation of large numbers of items with a small to medium sized group of people, and to do it quickly. The ...

Blind Estimation for Planning Poker
When helping people learn Planning Poker I always ask what will happen if one person plays/says their estimate before anyone else. Many people ...

Late Projects Caused By Poor Estimation and Other Red Herrings
Late Projects Caused By Poor Estimation and Other Red Herrings 12/08/2006 I've been seeing a pattern lately with Agile projects. It's not ...

Evolving Estimation Process
... yesterday. What I hope you can see from the photo is engagement of everyone in the conversation. It's quite unlike many tedious story estimation ...

Volvo Experimenting With 'Driver State Estimation' System
... announced it is experimenting with "driver sensors" to try cutting down on driver inattention while behind the wheel. The "Driver State Estimation," ...

BBC World Service poll: Why has the UK gone up in people's estimations?
People's opinions of the UK have improved markedly since 2012, according to a BBC World Service poll of more than 26,000 global citizens. BUt ...

Contract Estimation and Jarrod Saltalamacchia
Alex Skillin summarized the transactions in the catching market quite nicely; now that some of the dust has settled on the catching market, it’s ...