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Help with Matlab Problem

Any one know how to work this problem?
In this exercise you are to compute a power of the diagonalizable matrix A. Let A = pascal(5). Use the eigenvalue decomposition of A to calculate the ninth power of A. You cannot apply the power operator ^ to the matrix A.
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ankrunner (1)
1/20/2012 6:00:08 PM
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"Lynn Koch" <ankrunner@aol.com> wrote in message 
news:jfca37$r46$1@newscl01ah.mathworks.com...
> Any one know how to work this problem?
> In this exercise you are to compute a power of the diagonalizable matrix 
> A. Let A = pascal(5). Use the eigenvalue decomposition of A to calculate 
> the ninth power of A. You cannot apply the power operator ^ to the matrix 
> A.

AToNinth = (A+0)^9;

The exercise just said you couldn't apply ^ to A; it said nothing about the 
expression A+0.

The more serious answer is that this sounds like it's a homework problem and 
in general, the readers of this newsgroup won't help with homework problems 
unless the student shows what they've tried first. Show the group how you've 
started and you may receive some help; if you're not sure even where to 
begin, you should contact your teacher or TA and ask them to help you get 
started.

-- 
Steve Lord
slord@mathworks.com
To contact Technical Support use the Contact Us link on 
http://www.mathworks.com 

0
slord (13689)
1/20/2012 7:34:38 PM
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Hi, I am new on neural network toolbox. I am trying to use LVQ algorithm,but it is not working at all. Right now I am trying to train the network for a simple sine curve, but it is not trained according to the target. Can you help me with your suggestion, my function is y=sin(x); x is my input and y is my target output. I classified target results in four different classes. 0.5<=value<=1.0; class 1 0.0<=value<0.5; class 2 -0.5<=value<0.0; class 3 -1<=value<-0.5; class 4 I would highly appriciate if you help me with some idea, i am stucked here for a long time. Here is the code I am using, --------------------------------------------------- t=-5:.1:5; x=t; for i=1:length(x) y(i)=sin(x(i)); end for i=1:1:length(y) if(0.5<(y(1,i)) && (y(1,i))<=1) tc1(1,i)=1; end end for i=1:1:length(y) if(0<=(y(1,i)) && (y(1,i))<0.5) tc1(1,i)=2; end end for i=1:1:length(y) if(-0.5<=(y(1,i)) && (y(1,i))<0) tc1(1,i)=3; end end for i=1:1:length(y) if(-1.0<=(y(1,i)) && (y(1,i))<-0.5) tc1(1,i)=4; end end p1=x; check(1,:)=p1; check(2,:)=tc1; checkall=sortrows(check,2); p=checkall(1,:); tc=checkall(2,:); t=ind2vec(tc); targets=full(t); sc=16; calu(1,1)=sum(targets(1,:)); calu(2,1)=sum(targets(2,:)); calu(3,1)=sum(targets(3,:)); calu(4,1)=sum(targets(4,:)); c1=calu(1,1)/(sum(calu(1,1)+calu(2,1)+calu(3,1)+calu(4,1))); c2=calu(2,1)/(sum(calu(1,1)+calu(2,1)+calu(3,1)+calu(4,1))); c3=calu...

problem with parallel matlab
for i=1:size(APLocation,1) point=APLocation(i,:); parfor j=1:length (RXpoint) rssi(i,j) = LOSS(point,RXpoint(:,j)'); %%rssi having the signal strength from all AP's end end when i'm running the following code, i get the same value for each element of rssi (serially i get different results) where is my problem? Creating some fake data and and implementing a simple LOSS function, I do not see a different between the serial and parallel execution. Does LOSS use any persistent or global variables? function [ rssi rssi2 ] = foo APLocation = rand(10); RXpoint = rand(10) * 5; for i=1:size(APLocation,1) point=APLocation(i,:); parfor j=1:length (RXpoint) rssi(i,j) = LOSS(point,RXpoint(:,j)'); end end for i=1:size(APLocation,1) point=APLocation(i,:); for j=1:length (RXpoint) rssi2(i,j) = LOSS(point,RXpoint(:,j)'); end end end function rv = LOSS( a,b ) rv = sum( a+b ); end "michael" <bezenchu@gmail.com> wrote in message news:ht0t0k$fce$1@fred.mathworks.com... > for i=1:size(APLocation,1) > point=APLocation(i,:); > parfor j=1:length (RXpoint) > rssi(i,j) = LOSS(point,RXpoint(:,j)'); %%rssi having the signal > strength from all AP's > end > end > > when i'm running the following code, i get the same value for each element ...

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