add the frequencySpectrum.m to plot the power spectrum

frequencySpectrum.m

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+function [f,power] = frequencySpectrum(signal,freq_sampling,plt)
+%{
+function [f,power] = frequencySpectrum(signal,freq_sampling,plt)
+ex: [f,power] = frequencySpectrum(x, 40, 1)
+
+Task: to generate the power spectrm of a signal
+
+Inputs:
+    -signal: the signal that we want to get FFT
+    -freq_sampling: how many samples we want per second 
+
+Outputs:
+    -f: vector of frequency 
+    -power: power spectrum of the input signal 
+
+Author: Tikea TE 
+Date: 11/04/2025
+%}
+
+n = length(signal);  % this is our number of samples  
+
+% generate the frequency vector
+f = (0:n-1)*(freq_sampling/n); % fs/n is the frequency resolution, it tells how many hz are between each bin
+
+% generate the power vector
+y = fft(signal,n); % compute DFT of the signal with the same length
+power = abs(y).^2/n; % compute the power(spectrum) of the DFT of the signal
+
+% find the max value of the power and its index 
+[val,ind] = max(power); 
+
+% plotting the figure 
+if (plt)
+    figure;
+    subplot(1,3,1) % time plot 
+	t=0:1/freq_sampling:(n-1)/freq_sampling; % time range
+	plot(t, signal)
+	xticks(0:0.1*freq_sampling:n);
+	xticklabels(0:0.1:n/freq_sampling);
+	xlabel('Time (s)');
+	ylabel('Amplitude (a.u.)');
+
+    subplot(1,3,2) % linear frequency plot
+	plot(f,power, 'b*'); hold on;
+	plot(f,power, 'r');
+	xlabel('Frequency (Hz)')
+	ylabel('Power (a.u.)')
+
+	subplot(1,3,3) % log frequency plot
+	plot(f,10*log10(power/power(ind)));
+	xlabel('Frequency (Hz)')
+	ylabel('Power (dB)')
+end
+
+
+
+
+