An efficient sparse kernel adaptive filtering algorithm based on isomorphism between functional subspace and Euclidean space

Masa Aki Takizawa, Masahiro Yukawa

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

6 Citations (Scopus)

Abstract

The existing kernel filtering algorithms are classified into two categories depending on what space the optimization is formulated in. This paper bridges the two different approaches by focusing on the isomorphism between the dictionary subspace and a Euclidean space with the inner product defined by the kernel matrix. Based on the isomorphism, we propose a novel kernel adaptive filtering algorithm which adaptively refines the dictionary and thereby achieves excellent performance with a small dictionary size. Numerical examples show the efficacy of the proposed algorithm.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4508-4512
Number of pages5
ISBN (Print)9781479928927
DOIs
Publication statusPublished - 2014 Jan 1
Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: 2014 May 42014 May 9

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
CountryItaly
CityFlorence
Period14/5/414/5/9

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ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Takizawa, M. A., & Yukawa, M. (2014). An efficient sparse kernel adaptive filtering algorithm based on isomorphism between functional subspace and Euclidean space. In 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 (pp. 4508-4512). [6854455] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2014.6854455