Completed Analysis

midterm.m

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+clear all
+close all
+clc
+
+%%%%%%%%%%%%%%%%%%
+%function power = frequencySpectrum(signal, fs)
+%
+% Task: Display the power spectrum (lin and log scale) of a given signal
+%
+% Input:
+%	- signal: the input signal to process
+%	- fs: the sampling rate
+%
+% Output:
+%	- power: the power spectrum
+%
+%
+% Thomas Périn, thomas.perin@ecam.fr
+% 20/04/2023
+%%%%%%%%%%%%%%%%%%
+
+signal = csvread('unknownsignal.csv');
+fs = 300;                   %Sampling frequency
+n = length(signal);
+t = 0:1/fs:(n-1)/fs;
+windowDuration = 1;
+
+figure;
+plot(t, signal);
+title('Original Signal');
+xlabel('time (s)');
+ylabel('amplitude (a.u.)');
+
+%%%% Windowing %%%%
+rectangularWin = zeros(1, n);
+for l_sample=1:windowDuration*fs
+	rectangularWin(l_sample) = 1;
+end
+
+% plot rectangular window
+figure;
+plot(t, rectangularWin);
+title('Rectangular Window');
+xlabel('time (s)');
+ylabel('amplitude (a.u.)');
+
+% apply the rectangular window
+for l_sample=1:n
+	signal_rect(l_sample) = signal(l_sample) * rectangularWin(l_sample);
+end
+
+% plot rectangular signal
+figure;
+plot(t, signal_rect);
+title('Signal with Rectangular Windowing');
+xlabel('time (s)');
+ylabel('amplitude (a.u.)');
+
+
+%%%% Spectral Analisis %%%%
+% compute DFT of input signal
+y = fft(signal_rect, n);
+% power of the DFT
+power = abs(y).^2/n;
+
+figure;
+f = (0:n-1)*(fs/n);         % frequency range
+plot(f,power);
+title('Frequency Plot');
+xlabel('frequency (Hz)');
+ylabel('amplitude (a.u.)');
+
+idx = find(power(61:81) == max(power(61:81)));
+f(idx+60)
+
+