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Proceedings Paper

Wavelet transform adaptive filtering
Author(s): Laurence M. Dang
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Paper Abstract

An LMS adaptive filtering algorithm is presented utilizing wavelet transforms. Its performance is compared to DCT and Walsh-Hadamard transform-based adaptive filtering. The experimental analysis is performed in the case of the system identification of an unknown system or filter for stationary input signals. The results show some improvement in the weight modelling of the filter with comparable convergence rates. A new performance criteria, the diagonality factor, is introduced in order to show the specific effect of the wavelet transform on a signal. A Mean Average Difference is also utilized to compare the weight modelling performance of the various transform-based LMS adaptive filterings studied in this paper.

Paper Details

Date Published: 11 October 1994
PDF: 10 pages
Proc. SPIE 2303, Wavelet Applications in Signal and Image Processing II, (11 October 1994); doi: 10.1117/12.188800
Show Author Affiliations
Laurence M. Dang, Santa Clara Univ. (United States)

Published in SPIE Proceedings Vol. 2303:
Wavelet Applications in Signal and Image Processing II
Andrew F. Laine; Michael A. Unser, Editor(s)

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