Retake_Signal_Processing/retake.m

152 lines
3.6 KiB
Matlab

clear all
close all
clc
signal = csvread('unknownsignal.csv');
samplingFreq = 650;
t = (0:length(signal)-1)/samplingFreq;
signalDuration = 2;
windowDuration = signalDuration/2;
%%%%%%%%%%%%
%RECTANGULAR
%%%%%%%%%%%%
% create rectangular window
rectangularWin = zeros(1, length(t));
for l_sample=1:windowDuration*samplingFreq
rectangularWin(l_sample + signalDuration*samplingFreq/4) = 1;
end
% plot rectangular window
%~ figure;
%~ plot(t, rectangularWin);
% apply the rectangular window
for l_sample=1:length(t)
signal_rect(l_sample) = signal(l_sample) * rectangularWin(l_sample);
end
% plot signal windowed by rectangular window
%~ figure;
%~ plot(t, signal_rect);
% plot the frequency spectrum of this windowed signal
power_rect = frequencySpectrum(signal_rect, samplingFreq);
power = frequencySpectrum(signal, samplingFreq);
%%%%%%%%%%%%
%HAMMING
%%%%%%%%%%%%
hammingWin = zeros(1, length(t));
for l_sample=1:windowDuration*samplingFreq
hammingWin(l_sample+signalDuration*samplingFreq/4) = (0.5 - 0.5*cos(2*pi*(l_sample)/(signalDuration*samplingFreq/2)));
end
% plot Hamming window
%~ figure;
%~ plot(t, hammingWin);
% apply the Hamming window
for l_sample=1:length(t)
signal_hamming(l_sample) = signal(l_sample) * hammingWin(l_sample);
end
% plot signal windowed by rectangular window
%~ figure;
%~ plot(t, signal_hamming);
% plot the frequency spectrum of this windowed signal
power_hamming = frequencySpectrum(signal_hamming, samplingFreq);
%%%%%%%%%%%%
%HANNING
%%%%%%%%%%%%
hanningWin = zeros(1, length(t));
for l_sample=1:windowDuration*samplingFreq
hanningWin(l_sample+signalDuration*samplingFreq/4) = (0.54 - 0.46*cos(2*pi*(l_sample)/(signalDuration*samplingFreq/2)));
end
% plot Hanning window
%~ figure;
%~ plot(t, hanningWin);
% apply the Hanning window
for l_sample=1:length(t)
signal_hanning(l_sample) = signal(l_sample) * hanningWin(l_sample);
end
% plot signal windowed by rectangular window
%~ figure;
%~ plot(t, signal_hanning);
% plot the frequency spectrum of this windowed signal
power_hanning = frequencySpectrum(signal_hanning, samplingFreq);
%%%%%%%%%%%%
%BLACKMAN
%%%%%%%%%%%%
blackmanWin = zeros(1, length(t));
for l_sample=1:windowDuration*samplingFreq
blackmanWin(l_sample+signalDuration*samplingFreq/4) = (0.42 - 0.5 * cos(2*pi*(l_sample)/(signalDuration*samplingFreq/2)) + 0/08*cos(4*pi*(l_sample)/(windowDuration*samplingFreq/2)));
end
% plot Blackman window
%~ figure;
%~ plot(t, blackmanWin);
% apply the Blackman window
for l_sample=1:length(t)
signal_blackman(l_sample) = signal(l_sample) * blackmanWin(l_sample);
end
% plot signal windowed by rectangular window
%~ figure;
%~ plot(t, signal_blackman);
% plot the frequency spectrum of this windowed signal
power_blackman = frequencySpectrum(signal_blackman, samplingFreq);
%%%%%%%%%%%%
% GLOBAL PLOT
%%%%%%%%%%%%
figure;
plot(t, signal_rect, 'r'); hold on;
plot(t, signal_hamming, 'b');
plot(t, signal_hanning, 'g');
plot(t, signal_blackman, 'k');
xlabel('time (s)');
ylabel('amplitude (a.u.)');
legend('Rectangular', 'Hamming', 'Hanning', 'Blackman');
title('Temporal variation of a windowed cosine signal');
figure;
n = length(t);
f = (0:n-1)*(samplingFreq/n); % frequency range
plot(f,10*log10(power_rect/max(power_rect))); hold on;
plot(f,10*log10(power_hamming/max(power_hamming)));
plot(f,10*log10(power_hanning/max(power_hanning)));
plot(f,10*log10(power_blackman/max(power_blackman)));
xlim([0 20]);
ylim([-100 0]);
legend('Rectangular', 'Hamming', 'Hanning', 'Blackman');
xlabel('Frequency (Hz)')
ylabel('Power (dB)')