An Application of the LMS Algorithm In Smoothing Pseudo Wigner Distribution

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 e...

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Journal Title: IEEE Transactions on Signal Processing Vol. 41; no. 2; pp. 930 - 934
Authors: P. Davis, F. Allen, Moeness Amin
Format: Article
Published: Feb 1993
Subjects:
Online Access: Full Text
Summary: 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.
ISSN: 1053-587X