#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');

% Define the window length in seconds
window_length_sec = 0.5; % You can adjust this value based on your needs

% Convert window length to samples
window_length_samples = round(window_length_sec * Fs);

% Create the Rectangular window
rectangular_window = rectwin(window_length_samples);

% Create the Hamming window
hamming_window = hamming(window_length_samples);

% Create the Hanning window
hanning_window = hanning(window_length_samples);

% Create the Blackman window
blackman_window = blackman(window_length_samples);

% Apply each window and perform spectral analysis using FFT
windows = {'Rectangular', 'Hamming', 'Hanning', 'Blackman'};
window_functions = {rectangular_window, hamming_window, hanning_window, blackman_window};

for i = 1:length(windows)
    % Apply the current window to the signal
    current_window = window_functions{i} .* signal(1:window_length_samples);
    
    % Perform the Fast Fourier Transform (FFT) on the window
    fft_result = fft(current_window);
    
    % Compute the frequency axis for the FFT plot
    f = (0:length(current_window)-1) * Fs / length(current_window);
    
    % Identify the dominant frequencies (sine wave components) in the window
    % Set a threshold to filter out noise
    threshold = 50;
    dominant_indices = find(abs(fft_result) > threshold);
    
    % Display the dominant frequencies and their magnitudes for the current window
    disp(['Dominant Frequencies (Hz) - ', windows{i}, ' Window:']);
    disp(f(dominant_indices));
    disp(['Magnitudes - ', windows{i}, ' Window:']);
    disp(abs(fft_result(dominant_indices)));
    
    % Plot the magnitude spectrum of the current window
    figure;
    plot(f, abs(fft_result));
    xlabel('Frequency (Hz)');
    ylabel('Magnitude');
    title(['Magnitude Spectrum (FFT) of Mysterious Signal - ', windows{i}, ' Window']);
end