Dear readers, my question is on something that looks like a variation of the Karhunen-Loeve Transform. The normal Karhunen-Loeve Transform would be like this: for a signal u of length L and an adaptive FIR filter of order M, we compute the Autocorrelation Matrix and its eigenvectors. In Matlab: L=max(size(u)); ruu=xcorr(u,u)/L; M=16; Ruu=toeplitz(ruu(L:L+M-1)); % Correlation Matrix [V,lambda]=eig(Ruu); Then one can use the matrix V as the transformation matrix for the transform-domain LMS algorithm. Now I have found another variety of this: H=V*diag(sqrt(diag(lambda.^(-1))))*V'; and use H as the transformation matrix. This was also called Karhunen-Loeve transform, but it obviously is something different. However, it also seems to converge more quickly. I don't see why, though. Can anyone please tell me more about the matrix H?
Karhunen-Loeve and Transform-Domain LMS Algorithm
Started by ●May 15, 2006
Reply by ●June 5, 20062006-06-05