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Volumn 28, Issue 10, 2014, Pages 1065-1072

Sparse leaky-LMS algorithm for system identification and its convergence analysis

Author keywords

Leaky LMS; Sparse systems; System identification; ZA LMS

Indexed keywords

ADAPTIVE FILTERING; COST FUNCTIONS; IDENTIFICATION (CONTROL SYSTEMS); RELIGIOUS BUILDINGS; SHRINKAGE; STABILITY CRITERIA;

EID: 84907937049     PISSN: 08906327     EISSN: 10991115     Source Type: Journal    
DOI: 10.1002/acs.2428     Document Type: Article
Times cited : (28)

References (17)
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    • Robust zero-point attraction least mean square algorithm on near sparse system identification
    • Jin J, Qu Q, Gu Y. Robust zero-point attraction least mean square algorithm on near sparse system identification. IET Signal Processing 2013; 7(3). DOI: 10.1049/iet-spr.2012.0125.
    • (2013) IET Signal Processing , vol.7 , Issue.3
    • Jin, J.1    Qu, Q.2    Gu, Y.3
  • 10
    • 77949691635 scopus 로고    scopus 로고
    • 0norm constraint LMS algorithm for sparse system identification
    • 0norm constraint LMS algorithm for sparse system identification. IEEE Signal Processing Letters 2009; 16(9):774-777.
    • (2009) IEEE Signal Processing Letters , vol.16 , Issue.9 , pp. 774-777
    • Gu, Y.1    Jin, J.2    Mei, S.3
  • 11
    • 84859976621 scopus 로고    scopus 로고
    • Performance analysis of l0 norm constraint least mean square algorithm
    • Su G, Jin J, Gu Y, Wang J. Performance analysis of l0 norm constraint least mean square algorithm. IEEE Transactions on Signal Processing 2012; 60(5):2223-2235.
    • (2012) IEEE Transactions on Signal Processing , vol.60 , Issue.5 , pp. 2223-2235
    • Su, G.1    Jin, J.2    Gu, Y.3    Wang, J.4
  • 12
  • 16
    • 77954925431 scopus 로고    scopus 로고
    • Non-negative matrix factorization with sparseness constraints
    • Hoyer PO. Non-negative matrix factorization with sparseness constraints. Journal of Machine Learning Research 2001; 49:1208-1215.
    • (2001) Journal of Machine Learning Research , vol.49 , pp. 1208-1215
    • Hoyer, P.O.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.