Comparison of LMS and NLMS adaptive filters with a non-stationary input

Author

Eweda, Eweda

Author_Institution

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

fYear

2010

fDate

7-10 Nov. 2010

Firstpage

1630

Lastpage

1634

Abstract

The tracking performances of the LMS and NLMS algorithms are compared when the input of the adaptive filter is nonstationary. The analysis is done in the context of tracking a Markov plant. A periodic scenario of the variation of the input power is considered. The steady-state peak mean square deviation is used as the tracking performance measure. It is found that one algorithm outperforms the other depending on the values of the rate of variation of the input power, the minimum input power, the noise variance, and the mean square plant parameter increments.

Keywords

Markov processes; adaptive filters; least mean squares methods; Markov plant; normalized least mean square adaptive filter; performance measure tracking; steady-state peak mean square deviation; Adaptive filters; Algorithm design and analysis; Fluctuations; Least squares approximation; Noise; Signal processing algorithms; Steady-state; Adaptive Filtering; LMS Algorithm; NLMS Algorithm; Tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

978-1-4244-9722-5

Type

conf

DOI

10.1109/ACSSC.2010.5757814

Filename

5757814