Temporal Parallelization of Inference in Hidden Markov Models

This paper presents algorithms for the parallelization of inference in hidden Markov models (HMMs). In particular, we propose a parallel forward-backward type of filtering and smoothing algorithm as well as a parallel Viterbi-type maximum-a-posteriori (MAP) algorithm. We define associative elements...

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Bibliographic Details
Published in:	IEEE transactions on signal processing Vol. 69; pp. 4875 - 4887
Main Authors:	Hassan, Sakira, Sarkka, Simo, Garcia-Fernandez, Angel
Format:	Journal Article
Language:	English
Published:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Graphics processing units Hidden Markov models Inference Inference algorithms Markov chains Parallel forward-backward algorithm parallel max-product algorithm Parallel processing parallel sum-product algorithm parallel Viterbi algorithm Polytopes Signal processing algorithms Sum product algorithm Task analysis Viterbi algorithm
ISSN:	1053-587X, 1941-0476
Online Access:	Get full text
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