Global Stabilization of the Least Mean Fourth Algorithm

Author

Eweda, Eweda

Author_Institution

Dept. of Electr. Eng., Ajman Univ. of Sci. & Technol., Ajman, United Arab Emirates

Volume

60

Issue

3

fYear

2012

fDate

3/1/2012 12:00:00 AM

Firstpage

1473

Lastpage

1477

Abstract

The least mean fourth algorithm has several stability problems. Its stability depends on the variance and distribution type of the adaptive filter input, the noise variance, and the initialization of the filter weights. The present correspondence provides a global solution to all these stability problems. This is achieved by normalizing the weight vector update term by a term that is fourth order in the regressor and second order in the estimation error. The former property stabilizes the algorithm against the variance and distribution type of the filter input, while the latter stabilizes the algorithm against the noise variance and the weight initialization. The obtained algorithm is stable for all values of the step-size between 0 and 2. The stability of the algorithm is supported by simulations.

Keywords

adaptive filters; regression analysis; stability; vectors; adaptive filter input; filter weight initialization; fourth order regressor; global stabilization; least mean fourth algorithm; noise variance; second order estimation error; stability problem; weight vector normalization; Adaptive filters; Algorithm design and analysis; Signal processing algorithms; Signal to noise ratio; Stability analysis; Vectors; Adaptive filtering; least mean fourth algorithm; normalized least mean fourth algorithm;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/TSP.2011.2177976

Filename

6094232