Hybrid algorithms for maximum likelihood and maximum a posteriori sequence estimation

被引：0
|
作者：
Mahony, RE
Brushe, GD
Moore, JB
机构：
来源：
ISSPA 96 - FOURTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, PROCEEDINGS, VOLS 1 AND 2 | 1996年
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D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents two methods of processing data generated by a hidden Markov model (HMM) such that the resulting state estimates are related to both the maximum likelihood (ML) estimates (generated by the Viterbi algorithm) and maximum a posteriori (MAP) estimates (generated by the HMM forward-backward algorithm). Both algorithms contain a tuneable parameter which selects the tendency of the processing to replicate ML or MAP estimates. In the limit the algorithms reproduce the ML and MAP estimates exactly.
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页码：451 / 454
页数：4
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