Adaptive combination with improved performance for sparse system

Gyogwon Koo, Jae Jin Jeong, Seung Hun Kim, Sang Woo Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We propose an adaptive combination of a proportionate normalized least-mean-square with individual activation factors (IAF-PNLMS) and a normalized mean-square (NLMS) for the sparse system. The IAF-PNLMS has the fastest initial convergence rate among the algorithms for the sparse system. The NLMS has a low misalignment for various systems. To obtain both fast convergence rate and a low misalignment, we derive the proposed algorithm through adaptive combination algorithm of the IAF-PNLMS and the NLMS. We simulate to show the proposed algorithm has better performance than the conventional algorithms for the sparse system in terms of convergence rate and steady-state performance.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Industrial Technology, ICIT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages732-736
Number of pages5
ISBN (Electronic)9781467380751
DOIs
StatePublished - 19 May 2016
EventIEEE International Conference on Industrial Technology, ICIT 2016 - Taipei, Taiwan, Province of China
Duration: 14 Mar 201617 Mar 2016

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology
Volume2016-May

Conference

ConferenceIEEE International Conference on Industrial Technology, ICIT 2016
Country/TerritoryTaiwan, Province of China
CityTaipei
Period14/03/1617/03/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Fingerprint

Dive into the research topics of 'Adaptive combination with improved performance for sparse system'. Together they form a unique fingerprint.

Cite this