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On The Temporal Parallelisation of The Viterbi Algorithm

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A4 Artikkeli konferenssijulkaisussa

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en

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5

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31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings, pp. 2018-2022, European Signal Processing Conference

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This paper presents an algorithm to parallelise the Viterbi algorithm along the temporal dimension to compute the maximum a posteriori (MAP) trajectory estimate of a hidden Markov model. We reformulate the MAP estimation problem as an optimal control problem. The proposed algorithm uses a parallelisation algorithm developed for optimal control problems that first performs a backward value function pass and then a forward trajectory recovery pass. The parallel Viterbi algorithm then corresponds to a specialised backward optimal control problem with a forward value function pass and backward MAP-trajectory recovery pass. The algorithm is empirically tested by running numerical simulations on a multi-core central processing unit (CPU) and a graphics processing unit (GPU).

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Funding Information: The authors would like to thank Academy of Finland for funding. Publisher Copyright: © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

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Särkkä, S & García-Fernández, A F 2023, On The Temporal Parallelisation of The Viterbi Algorithm. in 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. European Signal Processing Conference, European Association For Signal and Image Processing, pp. 2018-2022, European Signal Processing Conference, Helsinki, Finland, 04/09/2023. https://doi.org/10.23919/EUSIPCO58844.2023.10289998

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