Adaptive signal processing through stochastic approximation

1 December 1970

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. 9, 202
https://doi.org/10.1109/sap.1970.270020

Abstract

One of the problems in signal processing is estimating the impulse response function of an unknown system. The well-known Wiener filter theory has been a powerful method in attacking this problem. In comparison, the use of stochastic approximation method as an adaptive signal processor is relatively new. This adaptive scheme can often be described by a recursive equation in which the estimated impulse response parameters are adjusted according to the gradient of a pre-determined error function. This paper illustrates by means of simple examples the application of stochastic approximation method as a single-channel adaptive processor. Under some conditions the expected value of its weight sequence converges to the corresponding Wiener optimum filter when the least-mean-square (LMS) error criterion is used.

Keywords

This publication has 3 references indexed in Scilit:

Adaptive antenna systems
Proceedings of the IEEE, 1967
The Design of High-Resolution Digital Filters
IEEE Transactions on Geoscience Electronics, 1966
A Stochastic Approximation Method
The Annals of Mathematical Statistics, 1951