DocumentCode :
1743200
Title :
Convergence analysis of the variable weight mixed-norm LMS-LMF adaptive algorithm
Author :
Zerguine, Azzedine ; Aboulnasr, Tyseer
Author_Institution :
Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
Volume :
1
fYear :
2000
fDate :
Oct. 29 2000-Nov. 1 2000
Firstpage :
279
Abstract :
In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. Sufficient and necessary conditions for the convergence of the algorithm are derived. Furthermore, bounds on the step size to ensure convergence of the LMF algorithm are also derived.
Keywords :
adaptive filters; convergence of numerical methods; filtering theory; least mean squares methods; minimisation; time-varying filters; convergence analysis; cost functions; objective function; step size; sufficient and necessary conditions; time varying weighting factor; variable weight mixed-norm LMS-LMF adaptive algorithm; weighted sum; Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Computer errors; Convergence; Cost function; Equations; Least squares approximation; Minerals; Petroleum;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
ISSN :
1058-6393
Print_ISBN :
0-7803-6514-3
Type :
conf
DOI :
10.1109/ACSSC.2000.910959
Filename :
910959
Link To Document :
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