spectrogram and FT times test

FT_times.m

@@ -0,0 +1,19 @@
+clear all
+close all
+clc
+
+[y, fs] = audioread("sound/modulator22.wav");
+times = [];
+item_num = 20;
+for j = 1:item_num
+  localtime = [];
+  for i = 0:1
+    t0 = clock ();
+    frequencySpectrum_noplot(y, fs, 0); %true does FFT, false DFT
+    localtime(i+1) = etime (clock (), t0);
+  endfor
+  times = [times; localtime];
+endfor
+
+printf('Average DFT time: %d \n', mean(times(1:item_num, 1)))
+printf('Average FFT time: %d \n', mean(times(1:item_num, 2)))

frequencySpectrum_noplot.m

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+function [power, duration] = frequencySpectrum_noplot(signal, fs, pad)
+%%%%%%%%%%%%%%%%%%
+%function power = frequencySpectrum(signal, fs, pad)
+%
+% Task: Display the power spectrum (lin and log scale) of a given signal
+%
+% Input:
+%	- signal: the input signal to process
+%	- fs: the sampling rate
+%	-pad: boolean if true, signal is padded with 0 to the next power of 2 -> FFT instead of DFT
+%
+% Output: 
+%	- power: the power spectrum
+%	
+%
+% Guillaume Gibert, guillaume.gibert@ecam.fr
+% 25/04/2022
+%%%%%%%%%%%%%%%%%%
+
+n = length(signal);        % number of samples
+
+if (pad)
+	n = 2^nextpow2(n);
+end
+
+tic
+y = fft(signal, n);% compute DFT of input signal
+duration = toc;
+
+power = abs(y).^2/n;    % power of the DFT
+
+[val, ind] = max(power); % find the mx value of DFT and its index
+
+t=0:1/fs:(n-1)/fs; % time range
+%pad signal with zeros
+if (pad)
+	signal = [ signal; zeros( n-length(signal), 1)];
+end
+
+f = (0:n-1)*(fs/n);     % frequency range
+
+
+
+

spectral_analysis.m

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+clear all
+close all
+clc
+
+[y, fs] = audioread("sound/modulator22.wav");
+%frequencySpectrum(y, fs, 0); %true does FFT, false DFT
+step_size = 5; %ms
+window_size = 30;%ms
+spectrogram(y, fs, step_size, window_size)