Gradient based variable forgetting factor RLS algorithm

An accurate new variable forgetting factor recursive least-square adaptive algorithm is derived. An improved mean square behaviour analysis is presented, which shows that the theoretical analysis and the simulation results are close to each other. The control of the forgetting factor is based on the...

Full description

Saved in:
Bibliographic Details
Published in:Signal processing Vol. 83; no. 6; pp. 1163 - 1175
Main Authors: So, C.F., Ng, S.C., Leung, S.H.
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.06.2003
Elsevier Science
Subjects:
Adaptive filters
Applied sciences
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Information, signal and communications theory
RLS algorithm
Signal and communications theory
Signal, noise
Telecommunications and information theory
Variable forgetting factor
RLS algorithm
Variable forgetting factor
Adaptive filters
Performance evaluation
Adaptive algorithm
Adaptive filter
Recursive algorithm
Mean square error
Algorithm performance
Least squares method
Recursive method
Signal processing
Gradient method
ISSN:0165-1684, 1872-7557
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:An accurate new variable forgetting factor recursive least-square adaptive algorithm is derived. An improved mean square behaviour analysis is presented, which shows that the theoretical analysis and the simulation results are close to each other. The control of the forgetting factor is based on the dynamic equation of the gradient of mean square error. Compared with other variable forgetting factor algorithms, the new algorithm provides fast tracking and small mean square model error, and its performance will not be degraded much even in low signal-to-noise ratios.
ISSN:0165-1684
1872-7557
DOI:10.1016/S0165-1684(03)00037-9