WienerIdentification - k = 1; %for eqMatrix. to be used for...

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% Wiener system identification. % %% clear all u=normrnd(0,2,1,600); % A white gaussian input sequence u with length %400 0 mean and standard deviation 2 e=normrnd(0,.2,1,600); % A white gaussian with zero mean and standart de %viation .2 with length 400. it is error term %obtain input and outputs of original system. yt = zeros(1,1200); %output of LTI system zt = zeros(1,600); %overall system's output ind= 0:1:600; %filter indices hi = [1 0.3 .15]; %filter coefficients yt = conv(u,hi); %Output of LTI system zt = yt(1,1:600).^2 +e; eqMatrix = zeros(10*19,3);
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Unformatted text preview: k = 1; %for eqMatrix. to be used for assignments for i = 1:17 eqMatrix(k:k+17-i,1)=u(1,4+i-1) - u(1,5+i-1:21)'; eqMatrix(k:k+17-i,2)=u(1,4+i-1-1) - u(1,5+i-1-1:20)'; eqMatrix(k:k+17-i,3)=u(1,4+i-1-1-1)- u(1,5+i-1-1-1:19)'; k = k+17-i+1; end [m1,s1,m2]=svd(eqMatrix); eqMatrixN = m1(:,1:3)*s1(1:3,1:3)*m2(1:3,:)'; rigSide = [0;0;0;randn(187,1)]; GrEqMatrix=[eqMatrix randn(190,187)]; hi_es = GrEqMatrix\rigSide ddd=hi_es/hi_es(1,1) ddd2=eqMatrix\rigSide;ddd2 = ddd2/ddd2(1,1);ddd3 = eqMatrixN\rigSide;ddd3=ddd3/ddd3(1,1)...
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This note was uploaded on 07/04/2011 for the course ECE 501 taught by Professor Deniz during the Spring '11 term at Istanbul Universitesi.

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