Stabilization of stochastic delayed neural networks with Markovian switching

In this paper, the mean square exponential stabilization problem is investigated for a class of stochastic delayed neural networks with Markovian Switching. After proposing an exponential stability condition, our attention is focused oil the design of a state feedback controller such that the stochastic delayed neural networks with Markovian switching is exponentially stable in mean square. Several stabilization criteria, delay-independent and delay-dependent ones. which are expressed in terms of a set of linear matrix inequalities (LMIs), are proposed to stabilize the stochastic delayed neural networks with Markovian switching exponentially. The usefulness and applicability of the developed results are illustrated by means of two numerical examples.