fft

SignalFFT.m

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+#Date: 19/07/2023
+#Author: Adrien COMBE
+#Description: Retake exam Signal Processing
+
+% Load the CSV file containing the signal
+signal = csvread('unknownsignal.csv');
+
+% Given sampling frequency Fs = 650 Hz
+Fs = 650;
+
+% Time vector
+t = (0:length(signal)-1) / Fs;
+
+% Plot the signal in the time domain
+figure;
+plot(t, signal);
+xlabel('Time (s)');
+ylabel('Amplitude');
+title('Mysterious Signal in Time Domain');
+
+% Compute the length of the signal
+N = length(signal);
+
+% Perform the Fast Fourier Transform (FFT)
+fft_result = fft(signal);
+
+% Compute the frequency axis for the FFT plot
+f = (0:N-1) * Fs / N;
+
+% Plot the magnitude spectrum of the signal
+figure;
+plot(f, abs(fft_result));
+xlabel('Frequency (Hz)');
+ylabel('Magnitude');
+title('Magnitude Spectrum (FFT) of Mysterious Signal');
+
+% Identify the dominant frequencies (sine wave components)
+% Set a threshold to filter out noise
+threshold = 50;
+
+% Find the indices of dominant frequencies above the threshold
+dominant_indices = find(abs(fft_result) > threshold);
+
+% Extract the dominant frequencies and their magnitudes
+dominant_frequencies = f(dominant_indices);
+dominant_magnitudes = abs(fft_result(dominant_indices));
+
+% Display the dominant frequencies and their magnitudes
+disp('Dominant Frequencies (Hz):');
+disp(dominant_frequencies);
+disp('Magnitudes:');
+disp(dominant_magnitudes);