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Estimating state-space models in innovations form using the expectation maximisation algorithm

机译:使用期望最大化算法估计创新形式的状态空间模型

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The expectation maximisation (EM) algorithm has proven to be effective for a range of identification problems. Unfortunately, the way in which the EM algorithm has previously been applied has proven unsuitable for the commonly employed innovations form model structure. This paper addresses this problem, and presents a previously unexamined method of EM algorithm employment. The results are profiled, which indicate that a hybrid EM/gradient-search technique may in some cases outperform either a pure EM or a pure gradient-based search approach.
机译:期望最大化(EM)算法已被证明对一系列识别问题有效。不幸的是,事实证明,以前应用EM算法的方法不适用于通常采用的创新形式模型结构。本文解决了这个问题,并提出了一种以前未经审查的EM算法使用方法。分析结果表明,在某些情况下,混合EM /梯度搜索技术可能会胜过纯EM或基于梯度的纯搜索方法。

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