I built an LMS filter, and I have better convergence when I use an
alternate signal as input, than a DC(all x(n)>0) one. Did someone have an
explanation about it?
thanks

On Nov 29, 2:00=A0am, "mmoctar" <mmoc...@gmail.com> wrote:
> I built an LMS filter, and I have better convergence when I use an
> alternate signal as input, than a DC(all x(n)>0) one. Did someone have an
> explanation about it?
> thanks

The signal needs to be "persistently exciting" so the nearer it is to
white noise the better. You could use a square wave and it would work
when it changes.


SS

On Nov 28, 6:00=A0pm, "mmoctar" <mmoc...@gmail.com> wrote:
> I built an LMS filter, and I have better convergence when I use an
> alternate signal as input, than a DC(all x(n)>0) one. Did someone have an
> explanation about it?
> thanks

What you want from the training symbol? To experience the channel at
all frequencies or just at the DC?
A DC signal has a fourier transform of an impulse at the 0 frequency.
When this signal is passed through the channel, it can tell receiver
what channel did to the DC component only and not all the frequency.
So a better training symbol choice would be one that contains
components of all the frequencies. The only signal satisfying this
criteria is an impulse function (remember an impulse has fourier
transform of DC i.e. all the frequencies with the same amplitude).
This signal can probe the channel at all the frequencies. You can use
a truncated-in-time impulse function as training symbol.

Ubaid Abdullah
DSP & Communication Engineer
http://dspdotcomm.blogspot.com