A stopping rule for symbolic dynamic filtering

Yicheng Wen, Asok Ray

    Research output: Contribution to journalArticle

    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 1 2010

    All Science Journal Classification (ASJC) codes

    • Applied Mathematics

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