EXPONENTIALLY CONVERGENT BEHAVIOUR OF SIMPLE STOCHASTIC ADAPTIVE ESTIMATION ALGORITHMS.

Bitmead, Robert R.; Anderson, Brian D.O.

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EXPONENTIALLY CONVERGENT BEHAVIOUR OF SIMPLE STOCHASTIC ADAPTIVE ESTIMATION ALGORITHMS.

Date

1978

Authors

Bitmead, Robert R.

Anderson, Brian D.O.

Abstract

A stochastic algorithm, familiar from adaptive estimation, is introduced and its homogeneous part is shown to be exponentially convergent for a wide class of inputs, which need not be stationary. The implications of this convergence rate for the non-homogeneous algorithm in practical situations are qualitatively examined and a possible approach to improving performance in use is suggested.

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https://dspace-test.anu.edu.au/handle/1885/733729945

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DevOps Pure Testing

Source

Proceedings of the IEEE Conference on Decision and Control

Type

Conference article

DOI

10.1109/cdc.1978.267996

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Cultural advice

EXPONENTIALLY CONVERGENT BEHAVIOUR OF SIMPLE STOCHASTIC ADAPTIVE ESTIMATION ALGORITHMS.

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