Nonlinear spline adaptive filtering under maximum correntropy criterion

Siyuan Peng; Zongze Wu; Xie Zhang; Badong Chen

doi:10.1109/TENCON.2015.7373051

Nonlinear spline adaptive filtering under maximum correntropy criterion

Siyuan Peng
, Zongze Wu
, Xie Zhang
, Badong Chen

Faculty of Electronic and Information Engineering

South China University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

The nonlinear spline adaptive filtering under least mean square (SAF-LMS) uses the mean square error (MSE) based cost function to identify the Wiener-type nonlinear systems, which is rational under the assumption of Gaussian distributions. However, the mere second-order statistics are often not suitable for nonlinear and/or non-Gaussian systems. To address this issue, a new nonlinear adaptive filter, called nonlinear spline adaptive filtering under maximum correntropy criterion (SAF-MCC), is proposed in this work. Compared with the SAF-LMS, the SAF-MCC uses the maximum correntropy criterion (MCC) to replace the MSE criterion to improve the convergence performance especially in heavy-tailed non-Gaussian environments. Simulation results confirm the superior performance of the new algorithm.

Original language	English
Title of host publication	TENCON 2015 - 2015 IEEE Region 10 Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479986415
DOIs	https://doi.org/10.1109/TENCON.2015.7373051
State	Published - 5 Jan 2016
Event	35th IEEE Region 10 Conference, TENCON 2015 - Macau, Macao Duration: 1 Nov 2015 → 4 Nov 2015

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume	2016-January
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Conference

Conference	35th IEEE Region 10 Conference, TENCON 2015
Country/Territory	Macao
City	Macau
Period	1/11/15 → 4/11/15

Keywords

MCC
Spline Adaptive Filter
Wiener system identification
impulsive noise

Access to Document

10.1109/TENCON.2015.7373051

Cite this

Peng, S., Wu, Z., Zhang, X., & Chen, B. (2016). Nonlinear spline adaptive filtering under maximum correntropy criterion. In TENCON 2015 - 2015 IEEE Region 10 Conference Article 7373051 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2016-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2015.7373051

@inproceedings{dc370989dde943edbf264f3a3089dfd4,

title = "Nonlinear spline adaptive filtering under maximum correntropy criterion",

abstract = "The nonlinear spline adaptive filtering under least mean square (SAF-LMS) uses the mean square error (MSE) based cost function to identify the Wiener-type nonlinear systems, which is rational under the assumption of Gaussian distributions. However, the mere second-order statistics are often not suitable for nonlinear and/or non-Gaussian systems. To address this issue, a new nonlinear adaptive filter, called nonlinear spline adaptive filtering under maximum correntropy criterion (SAF-MCC), is proposed in this work. Compared with the SAF-LMS, the SAF-MCC uses the maximum correntropy criterion (MCC) to replace the MSE criterion to improve the convergence performance especially in heavy-tailed non-Gaussian environments. Simulation results confirm the superior performance of the new algorithm.",

keywords = "MCC, Spline Adaptive Filter, Wiener system identification, impulsive noise",

author = "Siyuan Peng and Zongze Wu and Xie Zhang and Badong Chen",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 35th IEEE Region 10 Conference, TENCON 2015 ; Conference date: 01-11-2015 Through 04-11-2015",

year = "2016",

month = jan,

day = "5",

doi = "10.1109/TENCON.2015.7373051",

language = "英语",

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Peng, S, Wu, Z, Zhang, X & Chen, B 2016, Nonlinear spline adaptive filtering under maximum correntropy criterion. in TENCON 2015 - 2015 IEEE Region 10 Conference., 7373051, IEEE Region 10 Annual International Conference, Proceedings/TENCON, vol. 2016-January, Institute of Electrical and Electronics Engineers Inc., 35th IEEE Region 10 Conference, TENCON 2015, Macau, Macao, 1/11/15. https://doi.org/10.1109/TENCON.2015.7373051

Nonlinear spline adaptive filtering under maximum correntropy criterion. / Peng, Siyuan; Wu, Zongze; Zhang, Xie et al.
TENCON 2015 - 2015 IEEE Region 10 Conference. Institute of Electrical and Electronics Engineers Inc., 2016. 7373051 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2016-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Nonlinear spline adaptive filtering under maximum correntropy criterion

AU - Peng, Siyuan

AU - Wu, Zongze

AU - Zhang, Xie

AU - Chen, Badong

PY - 2016/1/5

Y1 - 2016/1/5

N2 - The nonlinear spline adaptive filtering under least mean square (SAF-LMS) uses the mean square error (MSE) based cost function to identify the Wiener-type nonlinear systems, which is rational under the assumption of Gaussian distributions. However, the mere second-order statistics are often not suitable for nonlinear and/or non-Gaussian systems. To address this issue, a new nonlinear adaptive filter, called nonlinear spline adaptive filtering under maximum correntropy criterion (SAF-MCC), is proposed in this work. Compared with the SAF-LMS, the SAF-MCC uses the maximum correntropy criterion (MCC) to replace the MSE criterion to improve the convergence performance especially in heavy-tailed non-Gaussian environments. Simulation results confirm the superior performance of the new algorithm.

AB - The nonlinear spline adaptive filtering under least mean square (SAF-LMS) uses the mean square error (MSE) based cost function to identify the Wiener-type nonlinear systems, which is rational under the assumption of Gaussian distributions. However, the mere second-order statistics are often not suitable for nonlinear and/or non-Gaussian systems. To address this issue, a new nonlinear adaptive filter, called nonlinear spline adaptive filtering under maximum correntropy criterion (SAF-MCC), is proposed in this work. Compared with the SAF-LMS, the SAF-MCC uses the maximum correntropy criterion (MCC) to replace the MSE criterion to improve the convergence performance especially in heavy-tailed non-Gaussian environments. Simulation results confirm the superior performance of the new algorithm.

KW - MCC

KW - Spline Adaptive Filter

KW - Wiener system identification

KW - impulsive noise

UR - https://www.scopus.com/pages/publications/84962179893

U2 - 10.1109/TENCON.2015.7373051

DO - 10.1109/TENCON.2015.7373051

M3 - 会议稿件

AN - SCOPUS:84962179893

T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON

BT - TENCON 2015 - 2015 IEEE Region 10 Conference

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 35th IEEE Region 10 Conference, TENCON 2015

Y2 - 1 November 2015 through 4 November 2015

ER -

Nonlinear spline adaptive filtering under maximum correntropy criterion

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