spectrum.m

matlabDigitalSigalProcess内有文件若干

function [Spec,f] = spectrum(varargin)
%SPECTRUM Power spectrum estimate of one or two data sequences.
%   P=SPECTRUM(X,NFFT,NOVERLAP,WIND) estimates the Power Spectral Density of
%   signal vector X using Welch's averaged periodogram method. The signal X
%   is divided into overlapping sections, each of which is detrended and 
%   windowed by the WINDOW parameter, then zero padded to length NFFT. The 
%   magnitude squared of the length NFFT DFTs of the sections are averaged 
%   to form Pxx.  P is a two column matrix P = [Pxx Pxxc]; the second column
%   Pxxc is the 95% confidence interval. The number of rows of P is NFFT/2+1
%   for NFFT even, (NFFT+1)/2 for NFFT odd, or NFFT if the signal X is comp-
%   lex. If you specify a scalar for WINDOW, a Hanning window of that length
%   is used.
%
%   [P,F] = SPECTRUM(X,NFFT,NOVERLAP,WINDOW,Fs) given a sampling frequency
%   Fs returns a vector of frequencies the same length as Pxx at which the 
%   PSD is estimated.  PLOT(F,P(:,1)) plots the power spectrum estimate 
%   versus true frequency.
%
%   [P, F] = SPECTRUM(X,NFFT,NOVERLAP,WINDOW,Fs,Pr) where Pr is a scalar 
%   between 0 and 1, overrides the default 95% confidence interval and 
%   returns the Pr*100% confidence interval for Pxx instead.
%
%   SPECTRUM(X) with no output arguments plots the PSD in the current
%   figure window, with confidence intervals.
%
%   The default values for the parameters are NFFT = 256 (or LENGTH(X),
%   whichever is smaller), NOVERLAP = 0, WINDOW = HANNING(NFFT), Fs = 2, 
%   and Pr = .95. You can obtain a default parameter by leaving it out
%   or inserting an empty matrix [], e.g. SPECTRUM(X,[],128).
%
%   P = SPECTRUM(X,Y) performs spectral analysis of the two sequences
%   X and Y using the Welch method. SPECTRUM returns the 8 column array
%      P = [Pxx Pyy Pxy Txy Cxy Pxxc Pyyc Pxyc]
%   where
%      Pxx  = X-vector power spectral density
%      Pyy  = Y-vector power spectral density
%      Pxy  = Cross spectral density
%      Txy  = Complex transfer function from X to Y = Pxy./Pxx
%      Cxy  = Coherence function between X and Y = (abs(Pxy).^2)./(Pxx.*Pyy)
%      Pxxc,Pyyc,Pxyc = Confidence range.
%   All input and output options are otherwise exactly the same as for the
%   single input case.
%   
%   SPECTRUM(X,Y) with no output arguments will plot Pxx, Pyy, abs(Txy),
%   angle(Txy) and Cxy in sequence, pausing between plots.
%
%   SPECTRUM(X,...,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) as long as it is last, e.g. SPECTRUM(X,'none');
%
%   See also PSD, CSD, TFE, COHERE, SPECGRAM, SPECPLOT, DETREND, PMEM,
%     PMTM, PMUSIC.
%   ETFE, SPA, and ARX in the Identification Toolbox.

%   Author(s): J.N. Little, 7-9-86
%   	   C. Denham, 4-25-88, revised
%   	   L. Shure, 12-20-88, revised
%   	   J.N. Little, 8-31-89, revised 
%   	   L. Shure, 8-11-92, revised 
%   	   T. Krauss, 4-15-93, revised
%   Copyright (c) 1988-98 by The MathWorks, Inc.
%   $Revision: 1.32 $  $Date: 1997/12/02 18:36:38 $

%   The units on the power spectra Pxx and Pyy are such that, using
%   Parseval's theorem: 
%
%        SUM(Pxx)/LENGTH(Pxx) = SUM(X.^2)/LENGTH(X) = COV(X)
%
%   The RMS value of the signal is the square root of this.
%   If the input signal is in Volts as a function of time, then
%   the units on Pxx are Volts^2*seconds = Volt^2/Hz.
%
%   Here are the covariance, RMS, and spectral amplitude values of
%   some common functions:
%         Function   Cov=SUM(Pxx)/LENGTH(Pxx)   RMS        Pxx
%         a*sin(w*t)        a^2/2            a/sqrt(2)   a^2*LENGTH(Pxx)/4
%Normal:  a*rand(t)         a^2              a           a^2
%Uniform: a*rand(t)         a^2/12           a/sqrt(12)  a^2/12
%   
%   For example, a pure sine wave with amplitude A has an RMS value
%   of A/sqrt(2), so A = SQRT(2*SUM(Pxx)/LENGTH(Pxx)).
%
%   See Page 556, A.V. Oppenheim and R.W. Schafer, Digital Signal
%   Processing, Prentice-Hall, 1975.

error(nargchk(1,8,nargin))
[msg,x,y,nfft,noverlap,window,Fs,p,dflag]=specchk(varargin);
error(msg)
if isempty(p),
	p = .95;   % default confidence interval even if not asked for
end

n = length(x);		% Number of data points
nwind = length(window);
if n < nwind    % zero-pad x (and y) if length less than the window length
    x(nwind)=0;  n=nwind;
    if ~isempty(y), y(nwind)=0;  end
end
x = x(:);		% Make sure x and y are column vectors
y = y(:);
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

if (isempty(y))	% Single sequence case.
	Pxx = zeros(nfft,1); Pxx2 = zeros(nfft,1);
	for i=1:k
                if strcmp(dflag,'linear')
                    xw = window.*detrend(x(index));
                elseif strcmp(dflag,'none')
                    xw = window.*(x(index));
                else
                    xw = window.*detrend(x(index),0);
                end
		index = index + (nwind - noverlap);
		Xx = abs(fft(xw,nfft)).^2;
		Pxx = Pxx + Xx;
		Pxx2 = Pxx2 + abs(Xx).^2;
	end
	% Select first half
	if ~any(any(imag(x)~=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
	else
		select = 1:nfft;
	end
	Pxx = Pxx(select);
	Pxx2 = Pxx2(select);
	cPxx = zeros(size(Pxx));
	if k > 1
		c = (k.*Pxx2-abs(Pxx).^2)./(k-1);
		c = max(c,zeros(size(Pxx)));
		cPxx = sqrt(c);
	end
	ff = sqrt(2)*erfinv(p);  % Equal-tails.
	Pxx = Pxx/KMU;
	Pxxc = ff.*cPxx/KMU;
	P = [Pxx Pxxc];
else
	Pxx = zeros(nfft,1); % Dual sequence case.
	Pyy = Pxx; Pxy = Pxx; Pxx2 = Pxx; Pyy2 = Pxx; Pxy2 = Pxx;

	for i=1:k
                if strcmp(dflag,'linear')
                    xw = window.*detrend(x(index));
		    yw = window.*detrend(y(index));
                elseif strcmp(dflag,'none')
                    xw = window.*(x(index));
		    yw = window.*(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);
		Yy2 = abs(Yy).^2;
		Xx2 = abs(Xx).^2;
		Xy  = Yy .* conj(Xx);
		Pxx = Pxx + Xx2;
		Pyy = Pyy + Yy2;
		Pxy = Pxy + Xy;
		Pxx2 = Pxx2 + abs(Xx2).^2;
		Pyy2 = Pyy2 + abs(Yy2).^2;
		Pxy2 = Pxy2 + Xy .* conj(Xy);
	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
	else
		select = 1:nfft;
	end

	Pxx = Pxx(select);
	Pyy = Pyy(select);
	Pxy = Pxy(select);
	Pxx2 = Pxx2(select);
	Pyy2 = Pyy2(select);
	Pxy2 = Pxy2(select);
	
	cPxx = zeros(size(Pxx));
	cPyy = cPxx;
	cPxy = cPxx;
	if k > 1
   		c = max((k.*Pxx2-abs(Pxx).^2)./(k-1),zeros(size(Pxx)));
   		cPxx = sqrt(c);
   		c = max((k.*Pyy2-abs(Pyy).^2)./(k-1),zeros(size(Pxx)));
   		cPyy = sqrt(c);
   		c = max((k.*Pxy2-abs(Pxy).^2)./(k-1),zeros(size(Pxx)));
   		cPxy = sqrt(c);
	end

	Txy = Pxy./Pxx;
	Cxy = (abs(Pxy).^2)./(Pxx.*Pyy);
	
	ff = sqrt(2)*erfinv(p);  % Equal-tails.

	Pxx = Pxx/KMU;
	Pyy = Pyy/KMU;
	Pxy = Pxy/KMU;
	Pxxc = ff.*cPxx/KMU;
	Pxyc = ff.*cPxy/KMU;
	Pyyc = ff.*cPyy/KMU;
	P = [Pxx Pyy Pxy Txy Cxy Pxxc Pyyc Pxyc];
end

freq_vector = (select - 1)'*Fs/nfft;
if nargout == 0,   % do plots
        newplot;
	c = [max(Pxx-Pxxc,0)  Pxx+Pxxc];
	c = c.*(c>0);
	semilogy(freq_vector,Pxx,freq_vector,c(:,1),'--',...
		freq_vector,c(:,2),'--');
	title('Pxx - X Power Spectral Density')
	xlabel('Frequency')
	if (isempty(y)),   % single sequence case
		return
	end
	pause

        newplot;
	c = [max(Pyy-Pyyc,0)  Pyy+Pyyc];
	c = c.*(c>0);
	semilogy(freq_vector,Pyy,freq_vector,c(:,1),'--',...
		freq_vector,c(:,2),'--');
	title('Pyy - Y Power Spectral Density')
	xlabel('Frequency')
	pause

        newplot;
	semilogy(freq_vector,abs(Txy));
	title('Txy - Transfer function magnitude')
	xlabel('Frequency')
	pause

        newplot;
	plot(freq_vector,180/pi*angle(Txy)), ...
	title('Txy - Transfer function phase')
	xlabel('Frequency')
	pause

        newplot;
	plot(freq_vector,Cxy);
 	title('Cxy - Coherence')
 	xlabel('Frequency')

elseif nargout ==1, 
	Spec = P;
elseif nargout ==2, 
	Spec = P;
	f = freq_vector;
end

function [msg,x,y,nfft,noverlap,window,Fs,p,dflag] = specchk(P)
%SPECCHK Helper function for SPECTRUM
%   SPECCHK(P) takes the cell array P and uses each cell as 
%   an input argument.  Assumes P has between 1 and 7 elements.

%   Author(s): T. Krauss, 4-6-93

msg = [];
if length(P{1})<=1
    msg = 'Input data must be a vector, not a scalar.';
    x = [];
    y = [];
elseif (length(P)>1),
    if (all(size(P{1})==size(P{2})) & (length(P{1})>1) ) | ...
       length(P{2})>1,   % 0ne signal or 2 present?
        % two signals, x and y, present
        x = P{1}; y = P{2}; 
        % shift parameters one left
        P(1) = [];
    else 
        % only one signal, x, present
        x = P{1}; y = []; 
    end
else  % length(P) == 1
    % only one signal, x, present
    x = P{1}; y = []; 
end

% now x and y are defined; let's get the rest

if length(P) == 1
    nfft = min(length(x),256);
    window = hanning(nfft);
    noverlap = 0;
    Fs = 2;
    p = [];
    dflag = 'linear';
elseif length(P) == 2
    if isempty(P{2}),   dflag = 'linear'; nfft = min(length(x),256); 
    elseif isstr(P{2}), dflag = P{2};       nfft = min(length(x),256); 
    else              dflag = 'linear'; nfft = P{2};   end
    window = hanning(nfft);
    noverlap = 0;
    Fs = 2;
    p = [];
elseif length(P) == 3
    if isempty(P{2}), nfft = min(length(x),256); else nfft=P{2};     end
    if isempty(P{3}),   dflag = 'linear'; noverlap = 0;
    elseif isstr(P{3}), dflag = P{3};       noverlap = 0;
    else              dflag = 'linear'; noverlap = P{3}; end
    window = hanning(nfft);
    Fs = 2;
    p = [];
elseif length(P) == 4
    if isempty(P{2}), nfft = min(length(x),256); else nfft=P{2};     end
    if isstr(P{4})
        dflag = P{4};
        window = hanning(nfft);
    else
        dflag = 'linear';
        window = P{4};  window = window(:);   % force window to be a column
        if length(window) == 1, window = hanning(window); end
        if isempty(window), window = hanning(nfft); end
    end
    if isempty(P{3}), noverlap = 0;  else noverlap=P{3}; end
    Fs = 2;
    p = [];
elseif length(P) == 5
    if isempty(P{2}), nfft = min(length(x),256); else nfft=P{2};     end
    window = P{4};  window = window(:);   % force window to be a column
    if length(window) == 1, window = hanning(window); end
    if isempty(window), window = hanning(nfft); end
    if isempty(P{3}), noverlap = 0;  else noverlap=P{3}; end
    if isstr(P{5})
        dflag = P{5};
        Fs = 2;
    else
        dflag = 'linear';
        if isempty(P{5}), Fs = 2; else Fs = P{5}; end
    end
    p = [];
elseif length(P) == 6
    if isempty(P{2}), nfft = min(length(x),256); else nfft=P{2};     end
    window = P{4};  window = window(:);   % force window to be a column
    if length(window) == 1, window = hanning(window); end
    if isempty(window), window = hanning(nfft); end
    if isempty(P{3}), noverlap = 0;  else noverlap=P{3}; end
    if isempty(P{5}), Fs = 2;     else    Fs = P{5}; end
    if isstr(P{6})
        dflag = P{6};
        p = [];
    else
        dflag = 'linear';
        if isempty(P{6}), p = .95;    else    p = P{6}; end
    end
elseif length(P) == 7
    if isempty(P{2}), nfft = min(length(x),256); else nfft=P{2};     end
    window = P{4};  window = window(:);   % force window to be a column
    if length(window) == 1, window = hanning(window); end
    if isempty(window), window = hanning(nfft); end
    if isempty(P{3}), noverlap = 0;  else noverlap=P{3}; end
    if isempty(P{5}), Fs = 2;     else    Fs = P{5}; end
    if isempty(P{6}), p = .95;    else    p = P{6}; end
    if isstr(P{7})
        dflag = P{7};
    else
        msg = 'DFLAG parameter must be a string.'; return
    end
end

% NOW do error checking
if (nfft<length(window)), 
    msg = 'Requires window''s length to be no greater than the FFT length.';
end
if (noverlap >= length(window)),
    msg = 'Requires NOVERLAP to be strictly less than the window length.';
end
if (nfft ~= abs(round(nfft)))|(noverlap ~= abs(round(noverlap))),
    msg = 'Requires positive integer values for NFFT and NOVERLAP.';
end
if ~isempty(p),
    if (prod(size(p))>1)|(p(1,1)>1)|(p(1,1)<0),
        msg = 'Requires confidence parameter to be a scalar between 0 and 1.';
    end
end
if min(size(x))~=1,
    msg = 'Requires vector (either row or column) input.';
end
if (min(size(y))~=1)&(~isempty(y)),
    msg = 'Requires vector (either row or column) input.';
end
if (length(x)~=length(y))&(~isempty(y)),
    msg = 'Requires X and Y be the same length.';
end