Gradient-based variable forgetting factor RLS algorithm in time-varying environments

In this paper, a new control mechanism for the variable forgetting factor (VFF) of the recursive least square (RLS) adaptive algorithm is presented. The control algorithm is basically a gradient-based method of which the gradient is derived from an improved mean square error analysis of RLS. The new...

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Bibliographic Details
Published in:	IEEE transactions on signal processing Vol. 53; no. 8; pp. 3141 - 3150
Main Authors:	Shu-Hung Leung, So, C.F.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.08.2005 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptive algorithm Algorithm design and analysis Algorithms Analytical models Applied sciences Control algorithms Control theory Detection, estimation, filtering, equalization, prediction Dynamics Equations Error analysis Errors Exact sciences and technology Information, signal and communications theory Least squares methods Mathematical analysis Mathematical models Mean square error analysis Mean square error methods Mean square errors Mean square values Resonance light scattering RLS Signal and communications theory Signal, noise Steady-state Studies Telecommunications and information theory time-varying Transient analysis variable forgetting factor Target tracking Adaptive algorithm Forgetting factor Correlation matrix Theoretical study Unsteady state Recursive algorithm Steady state Time variation Mean square error Simulation variable forgetting factor Correlation analysis Least squares method Recursive method RLS Mean square error analysis time-varying Fast algorithm Gradient method Signal to noise ratio
ISSN:	1053-587X, 1941-0476
Online Access:	Get full text
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