A stopping rule for symbolic dynamic filtering

Yicheng Wen, Asok Ray

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


One of the key issues in symbolic dynamic filtering (SDF) is how to obtain a lower bound on the length of symbol blocks for computing the state probability vectors of probabilistic finite-state automata (PFSA). Having specified an absolute error bound at a confidence level, this short work formulates a stopping rule by making use of Markov chain Monte Carlo (MCMC) computations.

Original languageEnglish (US)
Pages (from-to)1125-1128
Number of pages4
JournalApplied Mathematics Letters
Issue number9
StatePublished - Sep 2010

All Science Journal Classification (ASJC) codes

  • Applied Mathematics


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