Multikernel adaptive filtering

研究成果: Article査読

99 被引用数 (Scopus)

抄録

This paper exemplifies that the use of multiple kernels leads to efficient adaptive filtering for nonlinear systems. Two types of multikernel adaptive filtering algorithms are proposed. One is a simple generalization of the kernel normalized least mean square (KNLMS) algorithm , adopting a coherence criterion for dictionary designing. The other is derived by applying the adaptive proximal forward-backward splitting method to a certain squared distance function plus a weighted block l 1 norm penalty, encouraging the sparsity of an adaptive filter at the block level for efficiency. The proposed multikernel approach enjoys a higher degree of freedom than those approaches which design a kernel as a convex combination of multiple kernels. Numerical examples show that the proposed approach achieves significant gains particularly for nonstationary data as well as insensitivity to the choice of some design-parameters.

本文言語English
論文番号6203609
ページ(範囲)4672-4682
ページ数11
ジャーナルIEEE Transactions on Signal Processing
60
9
DOI
出版ステータスPublished - 2012 8 27
外部発表はい

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

フィンガープリント 「Multikernel adaptive filtering」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル