Accession Number:

ADA528428

Title:

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

Descriptive Note:

Conference paper preprint

Corporate Author:

WASHINGTON UNIV SEATTLE DEPT OF ELECTRICAL ENGINEERING

Personal Author(s):

Report Date:

2010-01-01

Pagination or Media Count:

9.0

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.

Subject Categories:

  • Physical Chemistry
  • Numerical Mathematics
  • Mechanics
  • Thermodynamics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE