Marginalized Viterbi algorithm for hierarchical hidden Markov models

作者：

Highlights：

• We consider the problem of finding the most likely state sequence for hierarchical HMMs.

• The generalized Viterbi algorithm finds the most likely whole level state sequence.

• We propose a marginalized Viterbi algorithm, which finds the most likely upper level state sequence.

• The marginalized Viterbi algorithm is more accurate in terms of upper level state sequence estimation.

摘要

Highlights•We consider the problem of finding the most likely state sequence for hierarchical HMMs.•The generalized Viterbi algorithm finds the most likely whole level state sequence.•We propose a marginalized Viterbi algorithm, which finds the most likely upper level state sequence.•The marginalized Viterbi algorithm is more accurate in terms of upper level state sequence estimation.

论文关键词：Time series data,Hierarchical HMM,Finding the most likely state sequence,Generalized Viterbi algorithm,Marginalized Viterbi algorithm

论文评审过程：Received 28 September 2012, Revised 29 May 2013, Accepted 3 June 2013, Available online 13 June 2013.

论文官网地址：https://doi.org/10.1016/j.patcog.2013.06.001