Convergence behavior of the normalized least mean fourth algorithm

Author

Zerguine, Azzedine

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

275

Abstract

The normalized least mean fourth (NLMF) algorithm is presented in this work and shown to have potentially faster convergence. Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. Sufficient conditions for the NLMF algorithm convergence in the mean are obtained and the analysis of the steady-state performance is carried out using the feedback approach. Simulation results confirm the performance of the NLMF algorithm.

Keywords

convergence of numerical methods; correlation methods; feedback; least mean squares methods; statistical analysis; LMF algorithm; NLMF algorithm; NLMS algorithm; convergence behavior; feedback approach; input data correlation statistics; normalized least mean fourth algorithm; performance; simulation results; steady-state performance; sufficient conditions; Adaptive filters; Algorithm design and analysis; Convergence; Eigenvalues and eigenfunctions; Feedback; Least squares approximation; Minerals; Petroleum; Statistics; Steady-state;

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.2000.910958

Filename

910958