Open AccessImproved l 0 ‐RLS adaptive filter
Author(s) -
Das B.K.,
Chakraborty M.
Publication year - 2017
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2017.3441
Subject(s) - recursive least squares filter , adaptive filter , kernel adaptive filter , filter (signal processing) , norm (philosophy) , algorithm , control theory (sociology) , computer science , mathematics , mathematical optimization , filter design , artificial intelligence , control (management) , political science , law , computer vision
In this Letter, the authors present an improved sparse recursive least squares (RLS) algorithm, which employs a novel approximation of the l 0 norm of the filter coefficient vector for regularising the RLS cost function. The proposed algorithm achieves improved performance over existing algorithms as demonstrated via numerical simulations.