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 Markov models, allowing for supervised learning of the class-conditional probability density models, and for likelihood evaluation of multicomponent signals.
Multicomponent signal classification using the PMHT algorithm
2002-01-01
523525 byte
Conference paper
Electronic Resource
English
Multicomponent Signal Classification using the PMHT Algorithm
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