Demos	Source Code of corr.num	Document
	` Correlation between noisy signals x = 0..2*pi len 128      ` a single cycle noise = 0.2..0.2 len 128 ` amplitude of noise randomize n1 = sin(x)+rand(noise)   ` first noise signal n2 = sin(2*x)+rand(noise) ` second noise signal ss1 = 0.25*cos(x^2)     ` first source signal ss2 = 0.25*cos(2.5*x^2) ` second source signal s1 = ss1+n1 ` first measured signal s2 = ss1+n2 ` second measured signal s3 = ss2+n1 ` third measured signal ` correlation without filtering func corr(y1,y2)    ft1 = fft(y1)  ft2 = fft(y2)  return real(ifft(ft1*conj(ft2))) ` correlation with filtering func corrf(y1,y2)    i = 2,3,127,128 ` low freq. components  ft1 = fft(y1)  ft1[i] = 0 ` filter out  ft2 = fft(y2)  ft2[i] = 0 ` filter out  return real(ifft(ft1*conj(ft2))) ` compute the correlations ` (to display the correlations around zero we must ` shift the arrays after the computation) ` correlations without low-pass filter corr12 = shifft(corr(s1,s2)) corr13 = shifft(corr(s1,s3)) ` correlations with low-pass filter corrf12 = shifft(corrf(s1,s2)) corrf13 = shifft(corrf(s1,s3)) xx = x-pi ` -pi to pi; used in the graphs
Demos	Copyright © 2004 KEDMI Scientific Computing. All Rights Reserved.	Document