Analysis on the Convergence Property of the Sub-RLS Algorithm

Kensaku FUJII  Mitsuji MUNEYASU  Takao HINAMOTO  Yoshinori TANAKA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E84-A   No.10   pp.2591-2594
Publication Date: 2001/10/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Digital Signal Processing
Keyword: 
sub-RLS algorithm,  convergence condition,  LS algorithm,  RLS algorithm,  maximum eigenvalue,  

Full Text: PDF>>
Buy this Article




Summary: 
The sub-recursive least squares (sub-RLS) algorithm estimates the coefficients of adaptive filter under the least squares (LS) criterion, however, does not require the calculation of inverse matrix. The sub-RLS algorithm, based on the different principle from the RLS algorithm, still provides a convergence property similar to that of the RLS algorithm. This paper first rewrites the convergence condition of the sub-RLS algorithm, and then proves that the convergence property of the sub-RLS algorithm successively approximates that of the RLS algorithm on the convergence condition.