MATLAB: The number of samples to overlap must be less than the length of the segments

digital signal processing

Can anyone correct this code and tell where I did wrong exactly ?

fs =16000; 
t=0:1/fs:0.5; 
signal=2*sin(2*pi*300*t);
noise=5*randn(1,length(signal)); 
input_speech=noise(1:8000)+signal(1:8000);
removal_sample=input_speech(1,6000:end); 
RS=removal_sample(1:256);
t_min=0.075;
t_max=0.100;
[STFT,Freq,Time] =spectrogram(RS+1i*eps,window,window_length,NFFT,fs);

Best Answer

%@Walter sir already mentioned define Window length and lenght of fft, its works
fs =16000; 
t=0:1/fs:0.5; 
signal=2*sin(2*pi*300*t);
noise=5*randn(1,length(signal)); 
input_speech=noise(1:8000)+signal(1:8000);
removal_sample=input_speech(1,6000:end); 
RS=removal_sample(1:256);
t_min=0.075;
t_max=0.100;
%Decide the FFT length
NFFT=1024; %For Example
[STFT,Freq,Time] =spectrogram(RS+1i*eps,window,length(window),NFFT,fs);

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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

MATLAB: Finding frequency and duration of an audio signal

You specified it to be 1 kHz, and 1 second duration, so it is just that:

fs=24000.0; % Sampling rate 
t=0:1/fs:1; % One sample each Ts=1/fs 
x=cos(2*pi*1000*t);
sound(x,fs);
L = numel(t);
fn = fs/2;
FTx = fft(x)/L;
Fv = linspace(0, 1, fix(L/2)+1)*fn;
Iv = 1:numel(Fv);
figure
plot(Fv, abs(FTx(Iv))*2)
grid
xlim([0 2000])

The Fourier transform plot demonstrates it.

Best Answer

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MATLAB: Manual spectrogram creation without using spectrogram command

MATLAB: Finding frequency and duration of an audio signal

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