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A stopping rule for symbolic dynamic filtering

✍ Scribed by Yicheng Wen; Asok Ray

Publisher
Elsevier Science
Year
2010
Tongue
English
Weight
263 KB
Volume
23
Category
Article
ISSN
0893-9659

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✦ Synopsis

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.

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