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Constrained least mean p-power error algorithm

  • South China University of Technology

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

6 Scopus citations

Abstract

In this paper, we develop a new constrained adaptive filtering algorithm, called the constrained least mean p-power error (CLMP) algorithm, which adopts the mean p-power error (MPE) as the adaptation cost. Compared with the original constrained least mean square (CLMS) algorithm, the CLMP, with a proper p value, can achieve much better performance especially in presence of impulsive noises. Convergence property of the CLMP is also studied. Simulation results are presented to demonstrate the excellent performance of the new algorithm.

Original languageEnglish
Title of host publicationProceedings of the 35th Chinese Control Conference, CCC 2016
EditorsJie Chen, Qianchuan Zhao, Jie Chen
PublisherIEEE Computer Society
Pages5160-5163
Number of pages4
ISBN (Electronic)9789881563910
DOIs
StatePublished - 26 Aug 2016
Event35th Chinese Control Conference, CCC 2016 - Chengdu, China
Duration: 27 Jul 2016 → 29 Jul 2016

Publication series

NameChinese Control Conference, CCC
Volume2016-August
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference35th Chinese Control Conference, CCC 2016
Country/TerritoryChina
CityChengdu
Period27/07/16 → 29/07/16

Keywords

  • CLMP
  • CLMS
  • impulsive noise

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