Diagnosability of Stochastic Chemical Kinetic Systems: A Discrete Event Systems Approach (PREPRINT)

Abstract

We consider the problem of detecting events of interest in a stochastic chemical kinetic system from the perspective of discrete-event systems theory. We define a class of discrete-event systems, timed stochastic automata, that is well suited for modeling stochastic chemical kinetics and define tA- and tAA-diagnosability, two appropriate notions of diagnosability for this class of system. We develop the construction of a timed stochastic diagnoser that is used to provide online updates of the probability that an event of interest has occurred and a means for offline testing of diagnosability conditions. The results of the paper are illustrated using a model of stochastic gene expression.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
ADA528428

Entities

People

  • David Thorsley

Organizations

  • University of Washington

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Automata
  • Chemical Kinetics
  • Communication Systems
  • Differential Equations
  • Dynamics
  • Equations
  • Gene Expression
  • Kinetics
  • Linear Differential Equations
  • Markov Chains
  • Markov Processes
  • Molecules
  • Mrna
  • Probability
  • Probability Distributions
  • Systems Approach
  • Trajectories

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