MATLAB: Do I receive an error when I use the SPECTROGRAM function if the length of the window is equal to the signal length in Signal Processing Toolbox 6.13 (R2010a)

Signal Processing Toolbox

I try to plot the spectrogram of a signal using the following code (data file attached):

load emg;
x = emg;
lenx = length(x);
window = ones(1, lenx);
nfft = lenx/8; 
fs = 1000;
noverlap = 32;
F = [1:1:fs/2];
spectrogram(x,window,noverlap,F,fs)

The error I receive is the following:

??? Error using ==> surf at 78

Z must be a matrix, not a scalar or vector.

Error in ==> spectrogram>displayspectrogram at 250

hndl = surf(args{:},'EdgeColor','none');

Error in ==> spectrogram at 184 displayspectrogram(t,f,Pxx,isFsnormalized,faxisloc);

Best Answer

The ability to have the length of the signal to be the same as the length of the window is not available for the SPECTROGRAM function in Signal Processing Toolbox 6.13 (R2010a).

As a workaround, use the IMAGESC function as follows:

T = 0:0.001:2;
X = chirp(T,100,1,200,'q');
[S, F, T, P] = spectrogram(X,128,120,128,1E3); 
imagesc(F, T(1), 10*log10(P(:,1).')); 
axis xy; axis tight; 
xlabel('Frequency (Hz)');
ylabel('Time');
title('Quadratic Chirp');

Related Solutions

MATLAB: How to plot spectrogram on log frequency scale

You have to get the data spectrogram produces and plot it separately:

T = 0:0.001:2;
X = chirp(T,100,1,200,'q');
[S,F,T] = spectrogram(X,128,120,128,1E3,'yaxis');
figure(1)
surf(T,F,abs(S))
view([0 90])
axis tight
xlabel('Time')
ylabel('Frequency')
set(gca,'YScale','log')
title 'Quadratic chirp'

This is the chirp signal from the spectrogram documentation. See the ‘Examples’ section for the linear scale of the same signal.

MATLAB: Manual spectrogram creation without using spectrogram command

hello

see below (myspecgram)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%





% load signal
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% data
[data,Fs] = audioread('myWAVaudiofile.wav');
channel = 1;
signal = data(:,channel);
samples = length(signal);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% FFT parameters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
NFFT = 4096;    % 
OVERLAP = 0.75;
% spectrogram dB scale
spectrogram_dB_scale = 100;  % dB range scale (means , the lowest displayed level is XX dB below the max level)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% options 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% decimate (if needed)
% NB : decim = 1 will do nothing (output = input)
decim = 2;
if decim>1
    signal = decimate(signal,decim);
    Fs = Fs/decim;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% display 2 : time / frequency analysis : spectrogram demo
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% [sg,fsg,tsg] = specgram(signal,NFFT,Fs,hanning(NFFT),floor(NFFT*OVERLAP));  
[sg,fsg,tsg] = myspecgram(signal,NFFT,Fs,OVERLAP);  
% FFT normalisation and conversion amplitude from linear to dB (peak)
sg_dBpeak = 20*log10(abs(sg))+20*log10(2/length(fsg));     % NB : X=fft(x.*hanning(N))*4/N; % hanning only
% saturation of the dB range : 
% saturation_dB = 60;  % dB range scale (means , the lowest displayed level is XX dB below the max level)
min_disp_dB = round(max(max(sg_dBpeak))) - spectrogram_dB_scale;
sg_dBpeak(sg_dBpeak<min_disp_dB) = min_disp_dB;
% plots spectrogram
figure(2);
imagesc(tsg,fsg,sg_dBpeak);colormap('jet');
axis('xy');colorbar('vert');grid
title([' Spectrogram / Fs = ' num2str(Fs) ' Hz / Delta f = ' num2str(fsg(2)-fsg(1)) ' Hz ']);
xlabel('Time (s)');ylabel('Frequency (Hz)');
function  [sg,freq_vector,time] = myspecgram(signal,nfft,Fs,Overlap)
% [sg,freq_vector,time] = myspecgram(signal,NFFT,Fs,hanning(NFFT),floor(NFFT*OVERLAP));
% FFT peak spectrogram of signal  (example sinus amplitude 1   = 0 dB after fft).
%   signal - input signal, 
%   Fs - Sampling frequency (Hz).
%   nfft - FFT window size
%   Overlap - buffer overlap % (between 0 and 0.95)
dt = 1/Fs;
signal = signal(:);
samples = length(signal);
% fill signal with zeros if its length is lower than nfft
if samples<nfft
    s_tmp = zeros(nfft,1);
    s_tmp((1:samples)) = signal;
    signal = s_tmp;
    samples = nfft;
end
% window : hanning
window = hanning(nfft);
window = window(:);
%    compute fft with overlap 
 offset = fix((1-Overlap)*nfft);
 spectnum = 1+ fix((samples-nfft)/offset); % Number of windows
%     % for info is equivalent to : 
%     noverlap = Overlap*nfft;
%     spectnum = fix((samples-noverlap)/(nfft-noverlap));	% Number of windows
    % main loop
    sg = [];
    for i=1:spectnum
        start = (i-1)*offset;
        sw = signal((1+start):(start+nfft)).*window;
        sg = [sg (abs(fft(sw))*4/nfft)];     % X=fft(x.*hanning(N))*4/N; % hanning only 
        time(i) = (start+nfft/2)*dt; % time defined as in the middle of the data buffer
    end
% one sidded fft spectrum  % Select first half 
    if rem(nfft,2)    % nfft odd
        select = (1:(nfft+1)/2)';
    else
        select = (1:nfft/2+1)';
    end
    
sg = sg(select,:);
freq_vector = (select - 1)*Fs/nfft;
end

Best Answer

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MATLAB: Manual spectrogram creation without using spectrogram command

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