Article ID Journal Published Year Pages File Type
407995 Neurocomputing 2011 7 Pages PDF
Abstract

This paper is concerned with the problem of finite-time stability analysis for uncertain stochastic delayed reaction–diffusion genetic regulatory networks. The parameter uncertainties are assumed to be norm-bounded, and the time delays are assumed to be time-varying. Based on the Lyapunov functional method, sufficient conditions ensuring the networks to be finite-time robustly stochastically stable are established. When there are no norm-bounded parameter uncertainties in the networks, a finite-time stochastic stability condition is also established. All the conditions are diffusion-dependent as well as delay-dependent. Numerical examples are given to illustrate the effectiveness of the proposed results.

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Physical Sciences and Engineering Computer Science Artificial Intelligence
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