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signalProcessingMidterm
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merge 'develop'

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Guillaume BONABAU 2024-03-18 08:46:09 +01:00
parent 56aeabf968 018ca87a67
commit 5e19f5550a
3 changed files with 18 additions and 12 deletions
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5
frequencySpectrum.m
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@ -1,4 +1,4 @@
function power = frequencySpectrum(signal, fs, resolution)
function power = frequencySpectrum(signal, fs, resolution,RoI)
%%%%%%%%%%%%%%%%%%
%function power = frequencySpectrum(signal, fs, pad)
%
@ -8,6 +8,7 @@ function power = frequencySpectrum(signal, fs, resolution)
% - signal: the input signal to process
% - fs: the sampling rate in Hz
% - resolution: frequency resolution in Hz, signal will be padded with zeros if necessary
% - RoI: region of interest
%
% Output:
% - power: the power spectrum
@ -52,12 +53,14 @@ subplot(1,3,2) % linear frequency plot
f = (0:n-1)*(fs/n); % frequency range
plot(f,power, 'b*'); hold on;
plot(f,power, 'r');
xlim(RoI);
title("Frequency Linear ");
xlabel('Frequency (Hz)')
ylabel('Power (a.u.)')
subplot(1,3,3) % log frequency plot
plot(f,10*log10(power/power(ind)));
xlim(RoI);
title("Frequency Log");
xlabel('Frequency (Hz)')
ylabel('Power (dB)')

23
main.m
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@ -1,6 +1,6 @@
%%%%%%%%%%%%%%%%%%%%%%
% UNKNOWN SIGNAL
% Sampling frequency: 300 Hz
% Sampling frequency: 200 Hz
% Duration; 2 s
% First second: 0.1Hz, 30 Hz, 30.5 Hz, 60 Hz, 61 Hz
% Second second: 0.1Hz, 32 Hz, 36 Hz, 64 Hz, 72 Hz
@ -14,7 +14,7 @@ signal = csvread('unknownsignal.csv');
%%%%%SIGNAL CHARACTERISTICS%%%%%
% sets sampling frequency
fps = 300; % -> freqMax of the signal should be < 150 Hz (Shannon-Nyquisit theorem), in practice freqMax < 60 Hz would be better
fps = 200; % -> freqMax of the signal should be < 150 Hz (Shannon-Nyquisit theorem), in practice freqMax < 60 Hz would be better
% computes the duration of the signal
duration = length(signal) / fps; % in s
@ -22,6 +22,9 @@ duration = length(signal) / fps; % in s
% estimates its original frequency resolution
resolution = fps / length(signal); % in Hz
%crop the Power spectrums over the region of interest
RoI=[5,20];
%%%%%STATIONARITY%%%%%
% temporal plot
figure;
@ -48,14 +51,14 @@ signal_2 = signal(end/2+1:end);
%%%%%SPECTRAL ANALYSIS (RECTANGULAR WINDOW)%%%%%
%plots power spectrum with rectangular window
% 1st part of the signal with 1 Hz resolution
frequencySpectrum(signal_1, fps, 1);
frequencySpectrum(signal_1, fps, 1, RoI);
% 1st part of the signal with 0.5 Hz resolution
frequencySpectrum(signal_1, fps, 0.5);
frequencySpectrum(signal_1, fps, 0.5, RoI);
% 2nd part of the signal with 1 Hz resolution
frequencySpectrum(signal_2, fps, 1);
frequencySpectrum(signal_2, fps, 1, RoI);
% 2nd part of the signal with 0.5 Hz resolution
frequencySpectrum(signal_2, fps, 0.5);
frequencySpectrum(signal_2, fps, 0.5, RoI);
@ -63,15 +66,15 @@ frequencySpectrum(signal_2, fps, 0.5);
%plots power spectrum with blackman window
signal_1_win = blackmanWin(signal_1);
% 1st part of the signal with 1 Hz resolution
frequencySpectrum(signal_1_win, fps, 1);
frequencySpectrum(signal_1_win, fps, 1, RoI);
% 1st part of the signal with 0.5 Hz resolution
frequencySpectrum(signal_1_win, fps, 0.5);
frequencySpectrum(signal_1_win, fps, 0.5, RoI);
signal_2_win = blackmanWin(signal_2);
% 2nd part of the signal with 1 Hz resolution
frequencySpectrum(signal_2_win, fps, 1);
frequencySpectrum(signal_2_win, fps, 1, RoI);
% 2nd part of the signal with 0.5 Hz resolution
frequencySpectrum(signal_2_win, fps, 0.5);
frequencySpectrum(signal_2_win, fps, 0.5, RoI);

2
unknownsignal.csv
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