Function Spectrogram
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function spectrogram(signal, samplingFreq, step_size, window_size)
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%%%%%%%%%%%%%%%%%%%%%%%
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%function spectrogram(signal, samplingFreq, step_size, window_size)
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% ex.: spectrogram(signal, samplingFreq, step_size, window_size)
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%
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% Task: Plot the spectrogram of a given signal
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%
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% Inputs:
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% -signal: temporal signal to analyse
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% -samplingFreq: sampling frequency of the temporal signal
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% -step_size: how often the power spectrum will be computed in ms
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% -window_size: size of the analysing window in ms
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%
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% Ouput: None
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%
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% author: Guillaume Gibert (guillaume.gibert@ecam.fr)
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% date: 14/03/2023
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%%%%%%%%%%%%%%%%%%%%%%%
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figure;
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subplot(2,1,1);
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t=0:1/samplingFreq:length(signal)/samplingFreq-1/samplingFreq;
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plot(t, signal');
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xlim([0 length(signal)/samplingFreq-1/samplingFreq]);
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ylabel('amplitude (norm. unit)');
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subplot(2,1,2);
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step = fix(step_size*samplingFreq/1000); % one spectral slice every step_size ms
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window = fix(window_size*samplingFreq/1000); % window_size ms data window
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fftn = 2^nextpow2(window); % next highest power of 2
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[S, f, t] = specgram(signal, fftn, samplingFreq, window, window-step);
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S = abs(S(2:fftn*4000/samplingFreq,:)); % magnitude in range 0<f<=4000 Hz.
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S = S/max(S(:)); % normalize magnitude so that max is 0 dB.
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S = max(S, 10^(-40/10)); % clip below -40 dB.
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S = min(S, 10^(-3/10)); % clip above -3 dB.
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imagesc (t, f, log(S)); % display in log scale
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set (gca, "ydir", "normal"); % put the 'y' direction in the correct direction
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xlabel('time (s)');
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ylabel('frequency (Hz)');
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