Adaptive volterra filtering using M-band wavelet transform

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications
PublisherIEEE Computer Society
Pages959-963
Number of pages5
ISBN (Print)1864354518, 9781864354515
DOIs
StatePublished - 1999 Jan 1
Event5th International Symposium on Signal Processing and Its Applications, ISSPA 1999 - Brisbane, QLD, Australia
Duration: 1999 Aug 221999 Aug 25

Publication series

NameISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications
Volume2

Other

Other5th International Symposium on Signal Processing and Its Applications, ISSPA 1999
CountryAustralia
CityBrisbane, QLD
Period99/08/2299/08/25

Fingerprint

Adaptive filtering
Discrete wavelet transforms
Autocorrelation
Wavelet transforms
Processing

Cite this

Kim, B. W., Lee, Y. M., Park, S., & Nam, S. W. (1999). Adaptive volterra filtering using M-band wavelet transform. In ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications (pp. 959-963). [815831] (ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/ISSPA.1999.815831
Kim, Byeong Woo ; Lee, Yong Min ; Park, Sung-kwon ; Nam, Sang Won. / Adaptive volterra filtering using M-band wavelet transform. ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications. IEEE Computer Society, 1999. pp. 959-963 (ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications).
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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.",
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Kim, BW, Lee, YM, Park, S & Nam, SW 1999, Adaptive volterra filtering using M-band wavelet transform. in ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications., 815831, ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications, vol. 2, IEEE Computer Society, pp. 959-963, 5th International Symposium on Signal Processing and Its Applications, ISSPA 1999, Brisbane, QLD, Australia, 99/08/22. https://doi.org/10.1109/ISSPA.1999.815831

Adaptive volterra filtering using M-band wavelet transform. / Kim, Byeong Woo; Lee, Yong Min; Park, Sung-kwon; Nam, Sang Won.

ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications. IEEE Computer Society, 1999. p. 959-963 815831 (ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications; Vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - 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.

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Kim BW, Lee YM, Park S, Nam SW. Adaptive volterra filtering using M-band wavelet transform. In ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications. IEEE Computer Society. 1999. p. 959-963. 815831. (ISSPA 1999 - Proceedings of the 5th International Symposium on Signal Processing and Its Applications). https://doi.org/10.1109/ISSPA.1999.815831