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Analysis on the Convergence Property of the Sub-RLS Algorithm
Kensaku FUJII Mitsuji MUNEYASU Takao HINAMOTO Yoshinori TANAKA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2001/10/01
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Digital Signal Processing
sub-RLS algorithm, convergence condition, LS algorithm, RLS algorithm, maximum eigenvalue,
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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.