cyclic_cross_periodogram.m

循环平稳信号谱相关函数

function S=cyclic_cross_periodogram(x,y,N,M,a,g)
%close all;
%clear all;
% CYCLIC_CROSS_PERIODOGRAM
% 
% 	       calculate the spectral correlation density function
%              of signals x and y using the cyclic cross periodogram
%              algorithm
%              
%              Input parameters are:
%              x,y signals
%              N   length of time window used for estimating frequency 
%                  segments
%              a   window used for smoothing segments
%              g   window for smoothing correlation
%              
% USAGE        S=cyclic_cross_periodogram(x,y,N,a,g)
%
%              e.g s=cyclic_cross_periodogram(s1,s1,64,'hamming','hamming')

lx=length(x);
if (length(y)~=lx)
  error('Time series x and y must be same length')
end


a=feval(a,N)';
g=feval(g,M)';
g=g/sum(g);
a=a/sum(a);

X=zeros(2*N+1);
Y=zeros(2*N+1);

Ts=1/N;
a=waitbar(0,'f iteration');
for f=-N:N
    waitbar((f+N+1)/(2*N+1))
  xf=x.*exp(-j*2*pi*f*(0:lx-1)*Ts);
  yf=y.*exp(-j*2*pi*f*(0:lx-1)*Ts);
    n_r=N:-1:1;
    X(f+N+1)=sum(a.*xf(n_r));
    Y(f+N+1)=conj(sum(a.*yf(n_r)));	
end
close(a)
h=waitbar(0,'alpha iteration');
S=zeros(N+1,N+1);
for alpha=-floor(N/2):floor(N/2)
    waitbar((alpha+N/2)/N);
  for f=-floor(N/2):floor(N/2)
    f1=f+floor(alpha/2)+(floor(-((M-1)/2)):floor((M-1)/2));
    f2=f-floor(alpha/2)+(floor(-((M-1)/2)):floor((M-1)/2));
    if ((abs(f1)<N)&(abs(f2)<N))
      S(f+floor(N/2)+1,floor(N/2)+alpha+1)=sum(g.*X(f1+N+1).*Y(f2+N+1))/M;
    end
  end
end
close(h);
alpha=-N/2:N/2;
f=-N/2:N/2;
mesh(f,alpha,abs(S));
xlabel('循环频率alpha');
ylabel('频率f');
zlabel('循环谱');