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

Masahiro Yukawa; Yuta Tawara; Masao Yamagishi; Isao Yamada

doi:10.1109/ISCAS.2012.6271878

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

Masahiro Yukawa, Yuta Tawara, Masao Yamagishi, Isao Yamada

Research output: Contribution to conference › Paper › peer-review

17 Citations (Scopus)

Abstract

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 language	English
Pages	2749-2752
Number of pages	4
DOIs	https://doi.org/10.1109/ISCAS.2012.6271878
Publication status	Published - 2012
Externally published	Yes
Event	2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 - Seoul, Korea, Republic of Duration: 2012 May 20 → 2012 May 23

Other

Other	2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012
Country/Territory	Korea, Republic of
City	Seoul
Period	12/5/20 → 12/5/23

ASJC Scopus subject areas

Hardware and Architecture
Electrical and Electronic Engineering

Access to Document

10.1109/ISCAS.2012.6271878

Cite this

@conference{749ee2eb31d14807aa3f52131f18ca1a,

title = "Sparsity-aware adaptive filters based on p-norm inspired soft-thresholding technique",

abstract = "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.",

author = "Masahiro Yukawa and Yuta Tawara and Masao Yamagishi and Isao Yamada",

year = "2012",

doi = "10.1109/ISCAS.2012.6271878",

language = "English",

pages = "2749--2752",

note = "2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 ; Conference date: 20-05-2012 Through 23-05-2012",

}

TY - CONF

T1 - Sparsity-aware adaptive filters based on p-norm inspired soft-thresholding technique

AU - Yukawa, Masahiro

AU - Tawara, Yuta

AU - Yamagishi, Masao

AU - Yamada, Isao

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84866634781&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84866634781&partnerID=8YFLogxK

U2 - 10.1109/ISCAS.2012.6271878

DO - 10.1109/ISCAS.2012.6271878

M3 - Paper

AN - SCOPUS:84866634781

SP - 2749

EP - 2752

T2 - 2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012

Y2 - 20 May 2012 through 23 May 2012

ER -