📄 csd.m
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function [Pxy, Pxyc, f] = csd(varargin)
%CSD Cross Spectral Density estimate.
% Pxy = CSD(X,Y,NFFT,Fs,WINDOW) estimates the Cross Spectral Density of
% signal vectors X and Y using Welch's averaged periodogram method. X and
% Y are divided into overlapping sections, each of which is detrended,
% then windowed by the WINDOW parameter, then zero-padded to length NFFT.
% The products of the length NFFT DFTs of the sections of X and Y are
% averaged to form Pxy. Pxy is length NFFT/2+1 for NFFT even, (NFFT+1)/2
% for NFFT odd, or NFFT if the either X or Y is complex. If you specify
% a scalar for WINDOW, a Hanning window of that length is used. Fs is the
% sampling frequency which doesn't effect the cross spectrum estimate
% but is used for scaling of plots.
%
% [Pxy,F] = CSD(X,Y,NFFT,Fs,WINDOW,NOVERLAP) returns a vector of frequen-
% cies the same size as Pxy at which the CSD is estimated, and overlaps
% the X and Y sections NOVERLAP samples.
%
% [Pxy, Pxyc, F] = CSD(X,Y,NFFT,Fs,WINDOW,NOVERLAP,P) where P is a scalar
% between 0 and 1, returns the P*100% confidence interval for Pxy.
%
% CSD(X,Y,...,DFLAG), where DFLAG can be 'linear', 'mean' or 'none',
% specifies a detrending mode for the prewindowed sections of X and Y.
% DFLAG can take the place of any parameter in the parameter list
% (besides X and Y) as long as it is last, e.g. CSD(X,Y,'mean');
%
% CSD with no output arguments plots the CSD in the current figure window,
% with confidence intervals if you provide the P parameter.
%
% The default values for the parameters are NFFT = 256 (or LENGTH(X),
% whichever is smaller), NOVERLAP = 0, WINDOW = HANNING(NFFT), Fs = 2,
% P = .95, and DFLAG = 'none'. You can obtain a default parameter by
% leaving it off or inserting an empty matrix [], e.g. CSD(X,Y,[],10000).
%
% See also PSD, COHERE, TFE
% ETFE, SPA, and ARX in the Identification Toolbox.
% Author(s): T. Krauss, 3-30-93
% Copyright (c) 1988-98 by The MathWorks, Inc.
% $Revision: 1.22 $ $Date: 1997/11/26 20:13:00 $
error(nargchk(2,8,nargin))
x = varargin{1};
y = varargin{2};
[msg,nfft,Fs,window,noverlap,p,dflag]=psdchk(varargin(3:end),x,y);
error(msg)
% compute CSD
window = window(:);
n = length(x); % Number of data points
nwind = length(window); % length of window
if n < nwind % zero-pad x , y if length is less than the window length
x(nwind)=0;
y(nwind)=0;
n=nwind;
end
x = x(:); % Make sure x is a column vector
y = y(:); % Make sure y is a column vector
k = fix((n-noverlap)/(nwind-noverlap)); % Number of windows
% (k = fix(n/nwind) for noverlap=0)
index = 1:nwind;
KMU = k*norm(window)^2; % Normalizing scale factor ==> asymptotically unbiased
% KMU = k*sum(window)^2;% alt. Nrmlzng scale factor ==> peaks are about right
Spec = zeros(nfft,1); Spec2 = zeros(nfft,1);
for i=1:k
if strcmp(dflag,'none')
xw = window.*x(index);
yw = window.*y(index);
elseif strcmp(dflag,'linear')
xw = window.*detrend(x(index));
yw = window.*detrend(y(index));
else
xw = window.*detrend(x(index),0);
yw = window.*detrend(y(index),0);
end
index = index + (nwind - noverlap);
Xx = fft(xw,nfft);
Yy = fft(yw,nfft);
Xy2 = Yy.*conj(Xx);
Spec = Spec + Xy2;
Spec2 = Spec2 + Xy2.*conj(Xy2);
end
% Select first half
if ~any(any(imag([x y])~=0)), % if x and y are not complex
if rem(nfft,2), % nfft odd
select = [1:(nfft+1)/2];
else
select = [1:nfft/2+1]; % include DC AND Nyquist
end
Spec = Spec(select);
Spec2 = Spec2(select);
else
select = 1:nfft;
end
freq_vector = (select - 1)'*Fs/nfft;
% find confidence interval if needed
if (nargout == 3)|((nargout == 0)&~isempty(p)),
if isempty(p),
p = .95; % default
end
confid = Spec*chi2conf(p,k)/KMU;
end
Spec = Spec*(1/KMU);
% set up output parameters
if (nargout == 3),
Pxy = Spec;
Pxyc = confid;
f = freq_vector;
elseif (nargout == 2),
Pxy = Spec;
Pxyc = freq_vector;
elseif (nargout == 1),
Pxy = Spec;
elseif (nargout == 0),
if ~isempty(p),
P = [Spec confid];
else
P = Spec;
end
newplot;
plot(freq_vector,10*log10(abs(P))), grid on
xlabel('Frequency'), ylabel('Cross Spectrum Magnitude (dB)');
end
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