An application of the LMS algorithm in smoothing pseudo-Wigner distribution

Author

Amin, Moeness G. ; Davis, Paul J. ; Allen, Fred, Jr.

Author_Institution

Dept. of Electr. Eng., Villanova Univ., PA, USA

Volume

41

Issue

2

fYear

1993

fDate

2/1/1993 12:00:00 AM

Firstpage

930

Lastpage

934

Abstract

It is shown that the least-mean-square (LMS) adaptive algorithm, if implemented in the frequency domain, can separate the autoterms from the cross terms in Wigner-Ville distributions. This separation is achieved over the process stationary interval, and as such, is more evident in a slowly varying environment. It is demonstrated that the LMS simulates an exponentially smoothed pseudo-Wigner distribution. The time constant of the smoothing window is inversely proportional to the step-size parameter used in the algorithm

Keywords

adaptive filters; filtering and prediction theory; frequency-domain analysis; least squares approximations; statistical analysis; LMS algorithm; Wigner-Ville distributions; autoterms; cross terms; exponentially smoothed pseudo-Wigner distribution; frequency domain adaptive filtering; smoothing window; time constant; Adaptive algorithm; Adaptive filters; Biomedical engineering; Frequency domain analysis; Kernel; Least squares approximation; Signal processing algorithms; Smoothing methods; Spectral analysis; Time frequency analysis;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.193229

Filename

193229