TRACKING PROPERTIES OF ADAPTIVE SIGNAL PROCESSING ALGORITHMS.

David C. Farden, Khalid Sayood

Research output: Contribution to conferencePaperpeer-review

8 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages466-469
Number of pages4
StatePublished - 1980
Externally publishedYes
EventUnknown conference - Denver, CO, USA
Duration: Apr 9 1980Apr 11 1980

Other

OtherUnknown conference
CityDenver, CO, USA
Period4/9/804/11/80

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'TRACKING PROPERTIES OF ADAPTIVE SIGNAL PROCESSING ALGORITHMS.'. Together they form a unique fingerprint.

Cite this