Adaptive exponential stabilization of neutral-type neural network with Lévy noise and Markovian switching parameters

In this paper, the problem of feedback controller designed to achieve adaptive exponential stabilization is investigated for stochastic neural networks of neutral type with Markovian switching parameters and the noise characterised by Lévy process. Based on Lyapunov functional theory and the generalized Itôs formula for neutral-type systems, the goal of this paper is to derive some criteria to ensure adaptive exponential stabilization for the stochastic neutral-type neural networks. Moreover, the update law of the control gain and the dynamic variation of the parameters of the system are provided. Finally, the theoretical analysis and potential of the stabilization criteria proposed in this paper are verified by a numerical example.