Robust filtering for stochastic genetic regulatory networks with time-varying delay

摘要: This paper addresses the robust filtering problem for a class of linear genetic regulatory networks (GRNs) with stochastic disturbances, parameter uncertainties and time delays. The are assumed to reside in polytopic region, disturbance is state-dependent described by scalar Brownian motion, time-varying delays enter into both translation process feedback regulation process. We aim estimate true concentrations mRNA protein designing filter such that, all admissible delays, disturbances as well uncertainties, augmented state estimation dynamics exponentially mean square stable an expected decay rate. A delay-dependent matrix inequality (LMI) approach first developed derive sufficient conditions that guarantee exponential stability dynamics, then gains parameterized terms solution set LMIs. Note LMIs can be easily solved using standard software packages. simulation example exploited order illustrate effectiveness proposed design procedures.