Adaptive volterra filtering using M-band wavelet transform

Author

Kim, Byeong-Woo ; Lee, Yong-Min ; Park, Sung-Kwon ; Nam, Sang-Won

Author_Institution

Dept. of Electr. & Comput. Eng., Hanyang Univ., Seoul, South Korea

Volume

2

fYear

1999

fDate

1999

Firstpage

959

Abstract

A new LMS adaptive Volterra filtering in the M-band wavelet transform domain is presented, where the input is pre-processed with MDWT (M-band discrete wavelet transform) being followed by power normalization. In particular, the pre-processing procedure leads to effective reduction of the eigenvalue spread of a Volterra input auto-correlation matrix, and thus improves the convergence rate of the adaptation process even in case of wide classes of input processes. To demonstrate the performance of the proposed approach, some simulation results are provided

Keywords

Volterra series; adaptive filters; convergence of numerical methods; correlation methods; discrete wavelet transforms; eigenvalues and eigenfunctions; filtering theory; least mean squares methods; LMS adaptive Volterra filtering; M-band discrete wavelet transform; M-band wavelet transform domain; Volterra input auto-correlation matrix; convergence rate; eigenvalue spread reduction; power normalization; pre-processing procedure; simulation results; Adaptive filters; Autocorrelation; Convergence; Discrete wavelet transforms; Eigenvalues and eigenfunctions; Filtering; Least squares approximation; Nonlinear filters; Wavelet domain; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 1999. ISSPA '99. Proceedings of the Fifth International Symposium on

Conference_Location

Brisbane, Qld.

Print_ISBN

1-86435-451-8

Type

conf

DOI

10.1109/ISSPA.1999.815831

Filename

815831