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