Sparsity-aware adaptive filters based on p-norm inspired soft-thresholding technique

Masahiro Yukawa, Yuta Tawara, Masao Yamagishi, Isao Yamada

Research output: Contribution to conferencePaperpeer-review

17 Citations (Scopus)


We propose a novel sparsity-aware adaptive filtering algorithm based on iterative use of weighted soft-thresholding. The weights are determined based on a rough local approximation of the p norm (0 < p < 1). The proposed algorithm operates the weighted soft-thresholding for enhancing the sparsity, following estimation error managements with the affine projection. The proposed weighting technique alleviates an extra bias of no benefit caused by shrinking dominant coefficients. The numerical examples demonstrate that the proposed weighting technique outperforms the existing one when the situation changes under the fixed parameter settings.

Original languageEnglish
Number of pages4
Publication statusPublished - 2012 Sep 28
Externally publishedYes
Event2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 - Seoul, Korea, Republic of
Duration: 2012 May 202012 May 23


Other2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering


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