merge 'develop'

frequencySpectrum.m

@@ -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)')

main.m

@@ -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);