Signal
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#Date: 20/04/2023
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#Author: Adrien COMBE
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#Description: Midterm Signal processing
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%The signal
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signal = csvread("unknownsignal.csv");
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%Sampling Frequency
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fs = 300; %Hz
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%Power spectrum
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frequencySpectrum(signal,fs)
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function power = frequencySpectrum(signal, fs)
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%%%%%%%%%%%%%%%%%%
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%function frequencySpectrum(signal, fs)
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%
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% Task: Display the power spectrum of a given signal
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%
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% Input:
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% - signal: the input signal to process
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% - fs: the sampling rate
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%
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% Output:
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% - power: power spectrum of the signal
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%
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%
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% Guillaume Gibert, guillaume.gibert@ecam.fr
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% 25/04/2022
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%%%%%%%%%%%%%%%%%%
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n = length(signal); % number of samples
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y = fft(signal, n);% compute DFT of input signal
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power = abs(y).^2/n; % power of the DFT
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[val, ind] = max(power); % find the mx value of DFT and its index
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% plots
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figure;
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subplot(1,3,1) % time plot
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t=0:1/fs:(n-1)/fs; % time range
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plot(t, signal)
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xticks(0:0.1*fs:n*fs);
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xticklabels(0:0.1:n/fs);
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xlabel('Time (s)');
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ylabel('Amplitude (a.u.)');
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subplot(1,3,2) % linear frequency plot
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f = (0:n-1)*(fs/n); % frequency range
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plot(f,power, 'b*'); hold on;
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plot(f,power, 'r');
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xlabel('Frequency (Hz)')
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ylabel('Power (a.u.)')
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subplot(1,3,3) % log frequency plot
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plot(f,10*log10(power/power(ind)));
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xlabel('Frequency (Hz)')
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ylabel('Power (dB)')
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