New delay-probability-distribution-dependent robust stability analysis for uncertain stochastic genetic regulatory networks with time-varying delays

This paper concerns the new delay-probability-distribution-dependent robust stability analysis for uncertain stochastic genetic regulatory networks (SGRNs) with time-varying delays. Based on model transformation, furthermore, by constructing a proper Lyaponov-Krasovskii functional and employing upper bound lemma on the reciprocally convex combination, we achieved the delay-probability-distribution-dependent criteria for the mean-square asymptotic stability of a class of SGRNs in terms of linear matrix inequalities (LMIs). The advantages of the proposed results compared some existing ones are to reduce computation complexity and conservativeness. Numerical examples show the effectiveness of the proposed approach.