Thresholding-based online algorithms of complexity comparable to sparse LMS methods

Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Stephen McLaughlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

This paper deals with a novel class of set-theoretic adaptive sparsity promoting algorithms of linear computational complexity. Sparsity is induced via generalized thersholding operators, which correspond to nonconvex penalties such as those used in a number of sparse LMS based schemes. The results demonstrate the significant performance gain of our approach, at comparable computational cost.

Original languageEnglish (US)
Title of host publication2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
Pages513-516
Number of pages4
DOIs
StatePublished - 2013
Event2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013 - Beijing, China
Duration: May 19 2013May 23 2013

Publication series

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

Other

Other2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
Country/TerritoryChina
CityBeijing
Period5/19/135/23/13

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