Merge branch 'develop'

hammingWin.m

@@ -27,6 +27,7 @@ windowDuration = signal_duration/2;
 
 hammingWin = zeros(1, length(t));
 
+% change sampling_freq/4 to shift the signal
 for l_sample=1:windowDuration*sampling_freq
 	hammingWin(l_sample+signal_duration*sampling_freq/4) = (0.54 - 0.46*cos(2*pi*(l_sample)/(signal_duration*sampling_freq/2)));
 end

hanningWin.m

@@ -27,6 +27,7 @@ windowDuration = signal_duration/2;
 
 hanningWin = zeros(1, length(t));
 
+% change sampling_freq/4 to shift the signal
 for l_sample=1:windowDuration*sampling_freq
 	hanningWin(l_sample+signal_duration*sampling_freq/4) = (0.5 - 0.5*cos(2*pi*(l_sample)/(signal_duration*sampling_freq/2)));
 end

main.m

@@ -0,0 +1,73 @@
+%%%%%%%%%%%%%%%%%%%%%%
+% UNKNOWN SIGNAL
+% Sampling frequency: 300 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
+%%%%%%%%%%%%%%%%%%%%%%
+
+% loads the signal package on Octave
+% pkg load signal
+
+% loads signal and its characteristics
+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
+
+% computes the duration of the signal
+duration = length(signal) / fps; % in s
+
+% estimates its original frequency resolution
+resolution = fps /  length(signal); % in Hz
+
+%%%%%STATIONARITY%%%%%
+% temporal plot
+figure;
+plot(signal);
+xticks(0:0.2*fps:length(signal)*fps);
+xticklabels(0:0.2:length(signal)/fps);
+xlabel('Time (s)');
+ylabel('Amplitude (a.u.)');
+
+% spectrogram
+step_size = 50; %ms
+window_size = 100; %ms
+spectrogram(signal, fps, step_size, window_size);
+
+% ccl: signal is not stationary, it is composed of 2 parts
+
+%%%%%SPLIT SIGNAL INTO 2 PARTS%%%%%
+% First part: [0 1s]
+signal_1 = signal(1:end/2);
+% Second part: [1s 2s]
+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);
+% 1st part of the signal with 0.5 Hz resolution
+frequencySpectrum(signal_1, fps, 0.5);
+
+% 2nd part of the signal with 1 Hz resolution
+frequencySpectrum(signal_2, fps, 1);
+% 2nd part of the signal with 0.5 Hz resolution
+frequencySpectrum(signal_2, fps, 0.5);
+
+
+
+%%%%%SPECTRAL ANALYSIS (BLACKMAN WINDOW)%%%%%
+%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);
+% 1st part of the signal with 0.5 Hz resolution
+frequencySpectrum(signal_1_win, fps, 0.5);
+
+signal_2_win = blackmanWin(signal_2);
+% 2nd part of the signal with 1 Hz resolution
+frequencySpectrum(signal_2_win, fps, 1);
+% 2nd part of the signal with 0.5 Hz resolution
+frequencySpectrum(signal_2_win, fps, 0.5);

rectWin.m

@@ -28,7 +28,7 @@ windowDuration = signal_duration/2;
 rectangularWin = zeros(1, length(t));
 
 for l_sample=1:windowDuration*sampling_freq
-	rectangularWin(l_sample + signal_duration) = 1;
+	rectangularWin(l_sample + signal_duration*sampling_freq/4) = 1;
 end
 
 figure;