A hybrid approach for sparse adaptive filters under highly colored inputs

Osamu Toda, Masahiro Yukawa, Shigenobu Sasaki, Hisakazu Kikuchi

Research output: Contribution to conferencePaper

Abstract

We address an adaptive filtering problem for sparse linear systems excited by highly colored input signals. A proportionate approach is known to accelerate the convergence speed by exploiting the sparseness of the systems, while a transformdomain approach is known to alleviate the decay of the convergence rate for highly colored inputs. We highlight the improved proportionate NLMS (IPNLMS) and transform-domain NLMS (TD-NLMS) algorithms. The present experimental results show that the gain of IPNLMS against TD-NLMS changes from positive to negative as the input auto-correlation becomes strong. We propose a hybrid approach of IPNLMS and TD-NLMS, taking the advantages of both algorithms by means of a timevariant convex combination of the two matrices employed by those algorithms. Numerical examples show the efficacy of the proposed algorithm.

Original languageEnglish
Pages78-82
Number of pages5
Publication statusPublished - 2011 Dec 1
Externally publishedYes
EventAsia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011 - Xi'an, China
Duration: 2011 Oct 182011 Oct 21

Other

OtherAsia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011
CountryChina
CityXi'an
Period11/10/1811/10/21

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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    Toda, O., Yukawa, M., Sasaki, S., & Kikuchi, H. (2011). A hybrid approach for sparse adaptive filters under highly colored inputs. 78-82. Paper presented at Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011, Xi'an, China.