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.
Descriptors:
Subject Categories:
- Physical Chemistry
- Numerical Mathematics
- Mechanics
- Thermodynamics