iir2.m

这是自适应信号处理的几个matlab程序

%IIR2 Problem 1.2.2
%
%   'ifile.mat' - input file containing:
%      I - members of ensemble
%      K - iterations
%      sigmax - standard deviation of input
%      thetaao, thetabo - coefficient vectors of plant
%      sigman - standard deviation of measurement noise
%      muv, mukappa - convergence factors
% 
%   'ofile.mat' - output file containing:
%      ind - sample indexes 
%      MSE - mean-square error 

clear all			% clear memory
load ifile;			% read input variables
N=length(thetaao);		% plant and filter den. order
M=length(thetabo)-1;		% plant and filter num. order 
N1=N+1;
N2=N+2;
M1=M+1;				% auxiliary parameters
MSE=zeros(K,1);			% prepare to accumulate MSE*I

for i=1:I,			% ensemble
   X=zeros(M1,1);		% initial input vector
   D1=zeros(N,1);		% desired signal initial memory
   kappa=zeros(N,1);		% initial reflection coefficients
   Dkappa=zeros(N,1);	% initial y derivatives with respect to kappa
   v=zeros(N1,1);		% output coefficients
   oldbh=zeros(N1,1);		% initial past backward residuals
   bh=zeros(N1,1);		% initial backward residuals
   fh=zeros(N1,1);		% initial forward residuals
   for l=1:N,
      oldbhp(:,l)=zeros(N1,1);	
			% initial past additional backward residuals
      bhp(:,l)=zeros(N1,1);	
			% initial additional backward residuals
      fhp(:,l)=zeros(N1,1);	
			% initial additional forward residuals
   end
   x=(rand(K,1)*2-1)*sqrt(3)*sigmax;	% input
   n=randn(K,1)*sigman;	% measurement noise 
   for k=1:K,			% iterations
      X=[x(k)
         X(1:N)];		% new input vector
      d=[thetaao;thetabo]'*[D1;X];
				% desired signal sample
      fh(N1)=x(k);
      for l=1:N,
         fh(N1-l)=fh(N2-l)-kappa(N1-l)*oldbh(N1-l);
         bh(N2-l)=kappa(N1-l)*fh(N1-l)+oldbh(N1-l);
      end
      bh(1)=fh(1);		% residuals
      y=v'*bh;			% output sample
      e=d+n(k)-y;		% error sample
      MSE(k)=MSE(k)+e^2;	% accumulate MSE*I
      D1=[d
          D1(1:N-1)];		% new desired signal memory
      v=v+muv*e*bh;		% new output coefficients
      for l=1:N,
         fhp(N1,l)=0;
         for ll=1:N,
            if N1-ll~=l,
               fhp(N1-ll,l)=fhp(N2-ll,l)-kappa(N1-ll)*oldbhp(N1-ll,l);
               bhp(N2-ll,l)=kappa(N1-ll)*fhp(N1-ll,l)+oldbhp(N1-ll,l);
            else,
               fhp(l,l)=fhp(l+1,l)-kappa(l)*oldbhp(l,l)+oldbh(l);
               bhp(l+1,l)=kappa(l)*fhp(l,l)+oldbhp(l,l)+fh(l);
            end
         end
         bhp(1,l)=fhp(1,l);	% additional residuals
         Dkappa(l)=v'*bhp(:,l);% y derivatives with respect to kappa
      end
      kappa=kappa+mukappa*e*Dkappa;	% new reflection coefficients
      %
      % stability test
      for l=1:N,
         if abs(kappa(l))>(1-eps),
            kappa(l)=sign(kappa(l))*(1-eps);
         end
      end
      % 
      % updated parameters
      oldbh=bh;
      oldbhp=bhp;
   end
end

ind=0:(K-1);			% sample indexes
MSE=MSE/I;			% calculate MSE
save ofile ind MSE;		% write output variables