Adaptive filtering based on wavelet transform

Author

Fengshi, Chen ; Xuejiang, Duan

Author_Institution

Dept. of Meas. & Control Eng., Xidian Univ., Xi´´an, China

fYear

1998

fDate

1998

Firstpage

457

Abstract

The performance analysis of a subband adaptive digital filter (SBADF) based on the wavelet transform is provided. While the convergence behaviour of the LMS algorithm to the optimum weight vector solution is better than that of the conventional adaptive filter, the computational complexity of the algorithm is reduced too. Computational simulations of the SBADF applied to an adaptive line enhancer are given to verify the above argument

Keywords

adaptive filters; adaptive signal processing; computational complexity; convergence of numerical methods; digital filters; filtering theory; least mean squares methods; optimisation; wavelet transforms; LMS algorithm; adaptive line enhancer; computational complexity; convergence behaviour; optimum weight vector solution; performance analysis; simulations; subband adaptive digital filter; wavelet transform; Adaptive filters; Computational complexity; Digital filters; Eigenvalues and eigenfunctions; Performance analysis; Signal processing algorithms; Signal resolution; Surface waves; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4325-5

Type

conf

DOI

10.1109/ICOSP.1998.770249

Filename

770249