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Tracking properties of adaptive signal processing algorithms

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2 Author(s)
D. Farden ; The University of Rochester, Rochester, New York ; K. Sayood

Adaptive signal processing algorithms are often used in order to "track" an unknown time-varying parameter vector. Such algorithms are typically some form of stochastic gradient-descent algorithm. The Widrow LMS algorithm is apparently the most frequently used. This work develops an upper bound on the norm-squared error between the parameter vector being tracked and the value obtained by the algorithm. The upper bound illustrates the relationship between the algorithm step-size and the maximum rate of variation in the parameter vector. Finally, some simple covariance decay-rate conditions are imposed to obtain a bound on the mean square error.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '80.  (Volume:5 )

Date of Conference:

Apr 1980