简单随机自适应估计算法的指数收敛性

1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes Pub Date : 1900-01-01 DOI:10.1109/CDC.1978.267996

R. Bitmead, B. O. Anderson

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引用次数: 6

摘要

引入了自适应估计中常见的一种随机算法，并证明了它的齐次部分对于一类不需要平稳的输入是指数收敛的。本文定性地分析了这种收敛速度对非齐次算法在实际情况下的影响，并提出了一种改进使用性能的可能方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Exponentially convergent behaviour of simple stochastic adaptive estimation algorithms

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 nonhomogeneous algorithm in practical situations are qualitatively examined and a possible approach to improving performance in use is suggested.

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来源期刊

1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes

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