Multicomponent signal classification using the PMHT algorithm

被引：0
|
作者：
Ainsleigh, P [1 ]
Luginbuhl, T [1 ]
机构：
[1] USN, Undersea Warfare Ctr, Newport, RI 02841 USA
来源：
PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOL I | 2002年
关键词：
classification; probablistic multi-hypothesis tracking; PMHT; hidden Markov model; HMM; continuous-state HMM; EM algorithm; forward-backward algorithm;
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：
The probabilistic multi-hypothesis tracking (PMHT) algorithm is extended for application to classification. The PMHT model is reformulated as a bank of continuous-state hidden Harkov models, allowing for supervised learning of the class-conditional probability density models, and for likelihood evaluation of multicomponent signals.
引用
收藏
页码：751 / 757
页数：5
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