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I intend to whiten the spectrum of a time series using a point-wise normalization in the frequency domain.

In my first test, it looks pretty good.

figure;
n = 2e3;
t = 1:n;
m = n/2+1;
f = linspace(0,1,m);
x = rand(1,n) - 0.5;
y = fft(x);
subplot(2,2,1); plot(t,x,'k'); 
axis tight; xlabel('t/s'); title('original signal x');
subplot(2,2,2); plot(f,abs(y(1:m)),'k'); 
axis tight; xlabel('f/hz'); title('original spectrum');
y1 = y ./ abs(y);
x1 = real(ifft(y1));
y2 = fft(x1);
x2 = real(ifft(y2));
subplot(2,2,3); plot(t,x1,'k',t,x2-x1,'r'); 
axis tight; xlabel('t/s'); title('whitened signal x1(black) and x2-x1(red)');
subplot(2,2,4); plot(f,abs(y1(1:m)),'k',f,abs(y2(1:m)),'r');
axis tight; xlabel('f/hz'); title('whitened spectrum y1(black) and y2(red)');

The spectrum is flat after whitening.

figure1

But when I windowed the spectrum, sth strange happened.

figure;
n = 2e3;
t = 1:n;
m = n/2+1;
f = linspace(0,1,m);
x = rand(1,n) - 0.5;
y = fft(x);
subplot(2,2,1); plot(t,x,'k'); 
axis tight; xlabel('t/s'); title('original signal x');
subplot(2,2,2); plot(f,abs(y(1:m)),'k'); 
axis tight; xlabel('f/hz'); title('original spectrum');
y1 = y ./ abs(y);  
k = n/10;
w = sin(linspace(0,pi/2,k));
y1(1:k) = y1(1:k) .* w;
y1(m:-1:m-k+1) = y1(m:-1:m-k+1) .* w;
y1(n-m+3:n) = y1(m-1:-1:2);    
x1 = real(ifft(y1));
y2 = fft(x1);
x2 = real(ifft(y2));
subplot(2,2,3); plot(t,x1,'k',t,x2-x1,'r'); 
axis tight; xlabel('t/s'); title('whitened signal x1(black) and x2-x1(red)');
subplot(2,2,4); plot(f,abs(y1(1:m)),'k',f,abs(y2(1:m)),'r');
axis tight; xlabel('f/hz'); title('whitened spectrum y1(black) and y2(red)');

As shown in subplot 3, x1 and x2 are the same (the difference is zero; see red line), but their spectrum in subplot 4 (black and red) is different.

After IFFT y1 to x1 and FFT x1 to y2, y2 differs from y1.

figure2

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  • $\begingroup$ you will notice a rough periodicity in the amplitude envelope of your "whitened signal". it's 12 cycles over the entire length. you might also notice that the spectrum of the original signal has its energy as a normalized frequency of about 1/12. i wonder if they have anything to do with each other? $\endgroup$ Commented May 11, 2014 at 4:06
  • $\begingroup$ How does it look when you plot y2? And what are you doing to get the spectrum of x2? It should be the same as y2. $\endgroup$ Commented May 11, 2014 at 4:54
  • $\begingroup$ Could you link to your signal x, so we can see for ourselves? $\endgroup$
    – Matt L.
    Commented May 11, 2014 at 8:10
  • $\begingroup$ @MackTuesday, abs(y2) is flat. The spectral magnitude of x2 is simply obtained by fft(x2); It's curious. $\endgroup$
    – wsdzbm
    Commented May 11, 2014 at 9:10
  • $\begingroup$ @MattL., it's arbitrary to generate a signal using random function. I edited the body text. $\endgroup$
    – wsdzbm
    Commented May 11, 2014 at 9:12

1 Answer 1

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As suggested by @Drazick, I post as an answer.

The good code according to the comments:

figure;
n = 2e3;
t = 1:n;
m = n/2+1;
f = linspace(0,1,m);
x = rand(1,n) - 0.5;
y = fft(x);
subplot(2,2,1); plot(t,x,'k'); 
axis tight; xlabel('t/s'); title('original signal x');
subplot(2,2,2); plot(f,abs(y(1:m)),'k'); 
axis tight; xlabel('f/hz'); title('original spectrum');
y1 = y ./ abs(y);
x1 = real(ifft(y1));
y2 = fft(x1);
x2 = real(ifft(y2));
subplot(2,2,3); plot(t,x1,'k',t,x2-x1,'r'); 
axis tight; xlabel('t/s'); title('whitened signal x1(black) and x2-x1(red)');
subplot(2,2,4); plot(f,abs(y1(1:m)),'k',f,abs(y2(1:m)),'r');
axis tight; xlabel('f/hz'); title('whitened spectrum y1(black) and y2(red)');

The spectrum is flat after whitening.

enter image description here

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