A New variable step-size algorithm using genetic-type search

S. H. Leung; C. Y. Chung; S. C. Ng

doi:10.1109/ISCAS.1994.408983

A New variable step-size algorithm using genetic-type search

S. H. Leung^*
, C. Y. Chung
, S. C. Ng

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

This paper proposes a new variable step-size algorithm using an evolutionary-type searching approach. The step-sizes of the adaptive filter are evolved regularly in a controlled manner to reduce the squared estimation error at each iteration. The algorithm improves the rate of convergence and achieves a low steady-state misadjustment. The performance analysis of the adaptive filter and simulation results are presented in the paper. The results show that the new algorithm outperforms the least mean square (LMS) algorithm with constant step-size considerably.

Original language	English
Title of host publication	Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94
Publisher	IEEE
Pages	381-384
Volume	2
ISBN (Print)	0-7803-1915-X
DOIs	https://doi.org/10.1109/ISCAS.1994.408983
Publication status	Published - May 1994
Event	1994 IEEE International Symposium on Circuits and Systems (ISCAS 1994) - London, United Kingdom Duration: 30 May 1994 → 2 Jun 1994

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)	0271-4310

Conference

Conference	1994 IEEE International Symposium on Circuits and Systems (ISCAS 1994)
Place	United Kingdom
City	London
Period	30/05/94 → 2/06/94

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@inproceedings{73ac9c56a26d4027b56066b33a184a93,

title = "A New variable step-size algorithm using genetic-type search",

abstract = "This paper proposes a new variable step-size algorithm using an evolutionary-type searching approach. The step-sizes of the adaptive filter are evolved regularly in a controlled manner to reduce the squared estimation error at each iteration. The algorithm improves the rate of convergence and achieves a low steady-state misadjustment. The performance analysis of the adaptive filter and simulation results are presented in the paper. The results show that the new algorithm outperforms the least mean square (LMS) algorithm with constant step-size considerably.",

author = "Leung, \{S. H.\} and Chung, \{C. Y.\} and Ng, \{S. C.\}",

year = "1994",

month = may,

doi = "10.1109/ISCAS.1994.408983",

language = "English",

isbn = "0-7803-1915-X",

volume = "2",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "IEEE",

pages = "381--384",

booktitle = "Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94",

address = "United States",

note = "1994 IEEE International Symposium on Circuits and Systems (ISCAS 1994) ; Conference date: 30-05-1994 Through 02-06-1994",

}

Leung, SH, Chung, CY & Ng, SC 1994, A New variable step-size algorithm using genetic-type search. in Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94. vol. 2, Proceedings - IEEE International Symposium on Circuits and Systems, IEEE, pp. 381-384, 1994 IEEE International Symposium on Circuits and Systems (ISCAS 1994), London, United Kingdom, 30/05/94. https://doi.org/10.1109/ISCAS.1994.408983

A New variable step-size algorithm using genetic-type search. / Leung, S. H.; Chung, C. Y.; Ng, S. C.
Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94. Vol. 2 IEEE, 1994. p. 381-384 (Proceedings - IEEE International Symposium on Circuits and Systems).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A New variable step-size algorithm using genetic-type search

AU - Leung, S. H.

AU - Chung, C. Y.

AU - Ng, S. C.

PY - 1994/5

Y1 - 1994/5

N2 - This paper proposes a new variable step-size algorithm using an evolutionary-type searching approach. The step-sizes of the adaptive filter are evolved regularly in a controlled manner to reduce the squared estimation error at each iteration. The algorithm improves the rate of convergence and achieves a low steady-state misadjustment. The performance analysis of the adaptive filter and simulation results are presented in the paper. The results show that the new algorithm outperforms the least mean square (LMS) algorithm with constant step-size considerably.

AB - This paper proposes a new variable step-size algorithm using an evolutionary-type searching approach. The step-sizes of the adaptive filter are evolved regularly in a controlled manner to reduce the squared estimation error at each iteration. The algorithm improves the rate of convergence and achieves a low steady-state misadjustment. The performance analysis of the adaptive filter and simulation results are presented in the paper. The results show that the new algorithm outperforms the least mean square (LMS) algorithm with constant step-size considerably.

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U2 - 10.1109/ISCAS.1994.408983

DO - 10.1109/ISCAS.1994.408983

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0-7803-1915-X

VL - 2

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

SP - 381

EP - 384

BT - Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94

PB - IEEE

T2 - 1994 IEEE International Symposium on Circuits and Systems (ISCAS 1994)

Y2 - 30 May 1994 through 2 June 1994

ER -

A New variable step-size algorithm using genetic-type search

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