Hybrid algorithms for maximum likelihood and maximum a posteriori sequence estimation

被引:0
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作者
Mahony, RE
Brushe, GD
Moore, JB
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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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