diff --git a/blackmanWin.m b/blackmanWin.m
new file mode 100644
index 0000000..1aeb2af
--- /dev/null
+++ b/blackmanWin.m
@@ -0,0 +1,42 @@
+function signal_win = blackmanWin(signal, signal_duration, sampling_freq, pad)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%function signal_win = blackmanWin(signal)
+%
+% Inputs:
+%	- signal: signal of interest
+%
+% Output:
+%	- signal_win: signal of interest on which a blackman window was applied
+%
+% Author: Guillaume Gibert, guillaume.gibert@ecam.fr
+% Date: 15/03/2024
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+% create the  temporal array
+t=-signal_duration/2:1/sampling_freq:(signal_duration/2)-1/sampling_freq;
+% window duration is half of signal duration
+windowDuration = signal_duration/2;
+
+
+blackmanWin = zeros(1, length(t));
+
+for l_sample=1:length(signal)
+	blackmanWin(l_sample) = (0.42 - 0.5 * cos(2*pi*(l_sample)/length(signal)) + 0/08*cos(4*pi*(l_sample)/length(signal)));
+end
+
+% plot Blackman window
+figure;
+title("Blackman Window"); hold on;
+plot(t, blackmanWin);
+
+% apply the Blackman window
+for l_sample=1:length(signal)
+	signal_win(l_sample) = signal(l_sample) * blackmanWin(l_sample);
+end
+
+figure;
+title("Original and Windowed signals"); hold on;
+plot(signal); hold on;
+plot(signal_win);
+
+frequencySpectrum(signal_win, sampling_freq/2,pad);
\ No newline at end of file
diff --git a/frequencySpectrum.m b/frequencySpectrum.m
new file mode 100644
index 0000000..67548c4
--- /dev/null
+++ b/frequencySpectrum.m
@@ -0,0 +1,55 @@
+function power = frequencySpectrum(signal, fs, pad)
+%%%%%%%%%%%%%%%%%%
+%function power = frequencySpectrum(signal, fs, pad)
+%
+% Task: Display the power spectrum (lin and log scale) of a given signal
+%
+% Input:
+%	- signal: the input signal to process
+%	- fs: the sampling rate
+%	- pad: pad the signal with zeros to the next power of 2
+%
+% Output:
+%	- power: the power spectrum
+%
+%
+% Guillaume Gibert, guillaume.gibert@ecam.fr
+% 25/04/2022
+%%%%%%%%%%%%%%%%%%
+
+n = length(signal);          % number of samples
+
+if (pad)
+	n_original = n;
+	n = 2^(nextpow2(n));
+	signal = [signal zeros(1, n-n_original)];
+end
+
+y = fft(signal, n);% compute DFT of input signal
+power = abs(y).^2/n;    % power of the DFT
+
+[val, ind] = max(power); % find the mx value of DFT and its index
+
+% plots
+figure;
+
+subplot(1,3,1) % time plot
+t=0:1/fs:(n-1)/fs; % time range
+plot(t, signal)
+xticks(0:0.1*fs:n*fs);
+xticklabels(0:0.1:n/fs);
+xlabel('Time (s)');
+ylabel('Amplitude (a.u.)');
+
+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');
+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)')
+
diff --git a/hammingWin.m b/hammingWin.m
new file mode 100644
index 0000000..19bbcae
--- /dev/null
+++ b/hammingWin.m
@@ -0,0 +1,48 @@
+function signal_win = hammingWin(signal, signal_duration, sampling_freq, pad)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%function signal_win = hammingWin(signal, signal_duration, sampling_freq, pad)
+% ex.: signal_win = hammingWin(signal, 2, 300, 1)
+%
+% Inputs:
+%   - signal: location of the signal to window
+%	- signal_duration: duration of the signal in seconds
+%	- sampling_freq: sampling frequency in Hz
+%   - pad: wether or not add zero padding (0 false; 1 true)
+%
+% Output:
+%	- signal_win:  signal of interest on which a hamming window was applied
+%
+% Author: Guillaume Gibert, guillaume.gibert@ecam.fr
+% Date: 04/03/2024
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+% create the  temporal array
+t=-signal_duration/2:1/sampling_freq:(signal_duration/2)-1/sampling_freq;
+% window duration is half of signal duration
+windowDuration = signal_duration/2;
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% creates the Hamming time window
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+hammingWin = zeros(1, length(t));
+
+for l_sample=1:windowDuration*sampling_freq
+	hammingWin(l_sample+signal_duration*sampling_freq/4) = (0.54 - 0.46*cos(2*pi*(l_sample)/(signal_duration*sampling_freq/2)));
+end
+
+figure;
+title("Hamming Window"); hold on;
+plot(t,hammingWin);
+
+% apply the window on input signal
+for l_sample=1:length(t)
+	signal_win(l_sample) = signal(l_sample) * hammingWin(l_sample);
+end
+
+figure;
+title("Original and Windowed signals"); hold on;
+plot(t, signal); hold on;
+plot(t, signal_win);
+
+frequencySpectrum(signal_win, sampling_freq/2,pad);
\ No newline at end of file
diff --git a/hanningWin.m b/hanningWin.m
new file mode 100644
index 0000000..d6ed0ef
--- /dev/null
+++ b/hanningWin.m
@@ -0,0 +1,48 @@
+function signal_win = hanningWin(signal, signal_duration, sampling_freq, pad)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%function signal_win = hanningWin(signal, signal_duration, sampling_freq, pad)
+% ex.: signal_win = hanningWin(signal, 2, 300, 1)
+%
+% Inputs:
+%   - signal: location of the signal to window
+%	- signal_duration: duration of the signal in seconds
+%	- sampling_freq: sampling frequency in Hz
+%   - pad: wether or not add zero padding (0=false; 1=true)
+%
+% Output:
+%	- signal_win:  signal of interest on which a hanning window was applied
+%
+% Author: Guillaume Gibert, guillaume.gibert@ecam.fr
+% Date: 04/03/2024
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+% create the  temporal array
+t=-signal_duration/2:1/sampling_freq:(signal_duration/2)-1/sampling_freq;
+% window duration is half of signal duration
+windowDuration = signal_duration/2;
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% creates the Hanning time window
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+hanningWin = zeros(1, length(t));
+
+for l_sample=1:windowDuration*sampling_freq
+	hanningWin(l_sample+signal_duration*sampling_freq/4) = (0.5 - 0.5*cos(2*pi*(l_sample)/(signal_duration*sampling_freq/2)));
+end
+
+figure;
+title("Hanning Window"); hold on;
+plot(t,hanningWin);
+
+% apply the window on input signal
+for l_sample=1:length(t)
+	signal_win(l_sample) = signal(l_sample) * hanningWin(l_sample);
+end
+
+figure;
+title("Original and Windowed signals"); hold on;
+plot(t, signal); hold on;
+plot(t, signal_win);
+
+frequencySpectrum(signal_win, sampling_freq/2,pad);
\ No newline at end of file
diff --git a/rectWin.m b/rectWin.m
new file mode 100644
index 0000000..2c83c6d
--- /dev/null
+++ b/rectWin.m
@@ -0,0 +1,48 @@
+function signal_win = rectWin(signal, signal_duration, sampling_freq, pad)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%function signal_win = rectWin(signal, signal_duration, sampling_freq, pad)
+% ex.: signal_win = rectWin(signal, 2, 300, 1)
+%
+% Inputs:
+%   - signal: location of the signal to window
+%	- signal_duration: duration of the signal in seconds
+%	- sampling_freq: sampling frequency in Hz
+%   - pad: wether or not add zero padding (0=false; 1=true)
+%
+% Output:
+%	- signal_win:  signal of interest on which a rectangular window was applied
+%
+% Author: Guillaume Gibert, guillaume.gibert@ecam.fr
+% Date: 04/03/2024
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+signal_duration = length(signal)/sampling_freq;
+% create the  temporal array
+t=-signal_duration/2:1/sampling_freq:(signal_duration/2)-1/sampling_freq;
+% window duration is half of signal duration
+windowDuration = signal_duration/2;
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% creates the Rectangular time window
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+rectangularWin = zeros(1, length(t));
+
+for l_sample=1:windowDuration*sampling_freq
+	rectangularWin(l_sample + signal_duration) = 1;
+end
+
+figure;
+title("Rectangular Window"); hold on;
+plot(t,rectangularWin);
+
+% apply the rectangular window
+for l_sample=1:length(t)
+	signal_win(l_sample) = signal(l_sample) * rectangularWin(l_sample);
+end
+
+figure;
+title("Original and Windowed signals"); hold on;
+plot(t, signal); hold on;
+plot(t, signal_win);
+
+frequencySpectrum(signal_win, sampling_freq/2,pad);
diff --git a/spectrogram.m b/spectrogram.m
new file mode 100644
index 0000000..ca44b95
--- /dev/null
+++ b/spectrogram.m
@@ -0,0 +1,35 @@
+function spectrogram(signal, samplingFreq, step_size, window_size)
+%%%%%%%%%%%%%%%%%%%%%%%
+%function spectrogram(signal, samplingFreq, step_size, window_size)
+% ex.:  spectrogram(signal, 300, 50, 1000)
+%
+% Task: Plot the spectrogram of a given signal
+%
+% Inputs:
+%	-signal: temporal signal to analyse 
+%	-samplingFreq: sampling frequency of the temporal signal
+% 	-step_size: how often the power spectrum will be computed in ms
+%	-window_size: size of the analysing window in ms
+%
+% Ouput: None
+%
+% author: Guillaume Gibert (guillaume.gibert@ecam.fr)
+% date: 14/03/2023
+%%%%%%%%%%%%%%%%%%%%%%%
+
+figure;
+	subplot(2,1,1);
+t=0:1/samplingFreq:length(signal)/samplingFreq-1/samplingFreq;
+plot(t, signal');
+xlim([0 length(signal)/samplingFreq-1/samplingFreq]);
+ylabel('Amplitude (norm. unit)');
+	
+	subplot(2,1,2);
+step = fix(step_size*samplingFreq/1000);     % one spectral slice every step_size ms
+window = fix(window_size*samplingFreq/1000);  % window_size ms data window
+
+
+[S, f, t] = specgram(signal);
+specgram(signal, 2^nextpow2(window), samplingFreq, window, window-step);
+xlabel('Time (s)');
+ylabel('Frequency (Hz)');