Fast forwards-backwards algorithm of generalized hidden Markov model

Hai Yang Chen, Xiao Guang Gao, Jun Feng Mei

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Dynamic Bayesian networks are an important tool for the nonlinear dynamical systems with uncertainty inference. A fast forwards-backwards algorithm is proposed by introducing a new computation method into the improved forwards-backwards (IFB) algorithm. The fast forwards algorithm and backwards algorithm are deduced in theory, and the two algorithms are combined to deduce the fast forwards-backwards algorithm. According to the complexity analysis, it's easy to see that the complexity of the proposed algorithm is lower. It is proved by the simulation experiments that the algorithm is correct and efficient.

Original languageEnglish
Pages (from-to)2175-2179
Number of pages5
JournalXi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
Volume34
Issue number10
DOIs
StatePublished - Oct 2012

Keywords

  • Complexity
  • Forwards-backwards algorithm
  • Hidden Markov model
  • Inference
  • Uncertainty

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