FFT filtering noise?
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Why I did I get a final signal like the first signal after denoising??
filename = 'koo.CSV';
M = csvread(filename);
x=M(:,3);
Y=M(:,4);
fs=250;
f=10;
subplot(3,2,1)
plot (x,Y,'b','linewidth',2)
title('Original Arc Signal')
xlabel('TIME,t(s)')
ylabel('VOLTAGE,V');
yrand = (rand(size(Y))-0.5) * 10;
z=Y + yrand;
subplot(3,2,2)
plot (x, z,'b', 'linewidth', 2)
title('Noisy Arc Signal')
xlabel('TIME,t(s)')
ylabel('VOLTAGE,V');
L=length(z);
NEFT=2^nextpow2(L);
z_fft=abs(fft(z,NEFT));
freq=fs/2*linspace(0,1.5,NEFT/2+1);
subplot(3,2,4);
plot(freq,z_fft(1:length(freq)));
o=5;
wn=[1 10]*2/fs;
[b,a]=butter(o,wn,'bandpass');
figure;freqz(b,a,1000,fs);
figure(1)
[h,w]=freqz(b,a,1000,fs);
subplot(3,2,3);
plot(w,20*log10(abs(h)));
z_filt=filter(b,a,z);
subplot(3,2,5);
ylim([0 20])
plot(x,z_filt,'b','linewidth', 2);

4 comentarios
Image Analyst
el 24 de Mzo. de 2019
You forgot to attach koo.csv.
What exact line of code is the filter actually being applied to the noisy version of the original signal?
hafis radzi
el 24 de Mzo. de 2019
Image Analyst
el 24 de Mzo. de 2019
It looks roughly like it if you invert the signal - I think it's just upside down.
hafis radzi
el 24 de Mzo. de 2019
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