Structural transformations of probabilistic finite state machines

I. Chattopadhyay, A. Ray

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


Probabilistic finite state machines have recently emerged as a viable tool for modelling and analysis of complex non-linear dynamical systems. This paper rigorously establishes such models as finite encodings of probability measure spaces defined over symbol strings. The well known Nerode equivalence relation is generalized in the probabilistic setting and pertinent results on existence and uniqueness of minimal representations of probabilistic finite state machines are presented. The binary operations of probabilistic synchronous composition and projective composition, which have applications in symbolic model-based supervisory control and in symbolic pattern recognition problems, are introduced. The results are elucidated with numerical examples and are validated on experimental data for statistical pattern classification in a laboratory environment.

Original languageEnglish (US)
Pages (from-to)820-835
Number of pages16
JournalInternational Journal of Control
Issue number5
StatePublished - May 2008

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications


Dive into the research topics of 'Structural transformations of probabilistic finite state machines'. Together they form a unique fingerprint.

Cite this