Adaptive filters based on the high order error statistics

Sung Ho Cho, Sang Duck Kim

Research output: Contribution to conferencePaper

7 Citations (Scopus)

Abstract

This paper presents convergence analyses of the stochastic gradient adaptive algorithms based on the high order error power criteria. In particular, our attention has focused on investigating the statistical behaviors of the least mean absolute third (LMAT) and the least mean fourth (LMF) adaptive algorithms. For each algorithm, under a set of mild assumptions, we have derived nonlinear evolution equations that characterize the mean and mean-squared behavior of the algorithm. Computer simulation examples show fairly good agreements between the theoretical and actual behaviors of the two algorithms.

Original languageEnglish
Pages109-112
Number of pages4
StatePublished - 1996 Dec 1
EventProceedings of the 1996 IEEE Asia Pacific Conference on Circuits and Systems - Seoul, South Korea
Duration: 1996 Nov 181996 Nov 21

Other

OtherProceedings of the 1996 IEEE Asia Pacific Conference on Circuits and Systems
CitySeoul, South Korea
Period96/11/1896/11/21

Fingerprint

Error statistics
Adaptive filters
Adaptive algorithms
Computer simulation

Cite this

Cho, S. H., & Kim, S. D. (1996). Adaptive filters based on the high order error statistics. 109-112. Paper presented at Proceedings of the 1996 IEEE Asia Pacific Conference on Circuits and Systems, Seoul, South Korea, .
Cho, Sung Ho ; Kim, Sang Duck. / Adaptive filters based on the high order error statistics. Paper presented at Proceedings of the 1996 IEEE Asia Pacific Conference on Circuits and Systems, Seoul, South Korea, .4 p.
@conference{0f5f8a8094184e7788620e6ced6ac673,
title = "Adaptive filters based on the high order error statistics",
abstract = "This paper presents convergence analyses of the stochastic gradient adaptive algorithms based on the high order error power criteria. In particular, our attention has focused on investigating the statistical behaviors of the least mean absolute third (LMAT) and the least mean fourth (LMF) adaptive algorithms. For each algorithm, under a set of mild assumptions, we have derived nonlinear evolution equations that characterize the mean and mean-squared behavior of the algorithm. Computer simulation examples show fairly good agreements between the theoretical and actual behaviors of the two algorithms.",
author = "Cho, {Sung Ho} and Kim, {Sang Duck}",
year = "1996",
month = "12",
day = "1",
language = "English",
pages = "109--112",
note = "null ; Conference date: 18-11-1996 Through 21-11-1996",

}

Cho, SH & Kim, SD 1996, 'Adaptive filters based on the high order error statistics' Paper presented at Proceedings of the 1996 IEEE Asia Pacific Conference on Circuits and Systems, Seoul, South Korea, 96/11/18 - 96/11/21, pp. 109-112.

Adaptive filters based on the high order error statistics. / Cho, Sung Ho; Kim, Sang Duck.

1996. 109-112 Paper presented at Proceedings of the 1996 IEEE Asia Pacific Conference on Circuits and Systems, Seoul, South Korea, .

Research output: Contribution to conferencePaper

TY - CONF

T1 - Adaptive filters based on the high order error statistics

AU - Cho, Sung Ho

AU - Kim, Sang Duck

PY - 1996/12/1

Y1 - 1996/12/1

N2 - This paper presents convergence analyses of the stochastic gradient adaptive algorithms based on the high order error power criteria. In particular, our attention has focused on investigating the statistical behaviors of the least mean absolute third (LMAT) and the least mean fourth (LMF) adaptive algorithms. For each algorithm, under a set of mild assumptions, we have derived nonlinear evolution equations that characterize the mean and mean-squared behavior of the algorithm. Computer simulation examples show fairly good agreements between the theoretical and actual behaviors of the two algorithms.

AB - This paper presents convergence analyses of the stochastic gradient adaptive algorithms based on the high order error power criteria. In particular, our attention has focused on investigating the statistical behaviors of the least mean absolute third (LMAT) and the least mean fourth (LMF) adaptive algorithms. For each algorithm, under a set of mild assumptions, we have derived nonlinear evolution equations that characterize the mean and mean-squared behavior of the algorithm. Computer simulation examples show fairly good agreements between the theoretical and actual behaviors of the two algorithms.

UR - http://www.scopus.com/inward/record.url?scp=0030420592&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0030420592

SP - 109

EP - 112

ER -

Cho SH, Kim SD. Adaptive filters based on the high order error statistics. 1996. Paper presented at Proceedings of the 1996 IEEE Asia Pacific Conference on Circuits and Systems, Seoul, South Korea, .