DocumentCode :
3199895
Title :
Decorrelated algorithms for faster adaptation
Author :
Liu, Ting ; Gazor, Saeed
Author_Institution :
Dept. of Electr. & Comput. Eng., Queen´´s Univ., Canada
Volume :
1
fYear :
2002
fDate :
26-30 Aug. 2002
Firstpage :
301
Abstract :
A new decorrelation filter is introduced on both input and desired signal to bring down:the correlation of input signal and additive noise. The new adaptive algorithms are derived and discussed in different cases. The introduced auxiliary adaptive whitening filter reduces the eigenvalue spread of the input autocorrelation matrix, thus accelerate the adaptation of the main filter. At the same time, the auxiliary filter reduces the effect of colored noise power spectra and hence reduces the misadjustment of the algorithm. The improvement obtained is considerable in most cases at the expense of a minor computational complexity.
Keywords :
adaptive filters; computational complexity; convergence of numerical methods; decorrelation; eigenvalues and eigenfunctions; matrix algebra; random noise; adaptive filter; adaptive whitening filter; additive noise; autocorrelation matrix; auxiliary filter; colored noise power spectra; computational complexity; convergence; decorrelation filter; eigenvalue spread; Acceleration; Adaptive algorithm; Adaptive filters; Additive noise; Colored noise; Convergence; Eigenvalues and eigenfunctions; Least squares approximation; Resonance light scattering; Wiener filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
Type :
conf
DOI :
10.1109/ICOSP.2002.1181050
Filename :
1181050
Link To Document :
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