Finite-time stabilization for positive Markovian jumping neural networks

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摘要

This paper addresses finite-time boundedness and stabilization problem for n-neuron uncertain positive Markovian jumping neural networks (MJNNs). Firstly, we analyze the positive MJNNs in the input-free case and then propose a sufficient condition to ensure the input-free finite-time boundedness. Then applying the state feedback scheme, a suitable finite-time stabilizable controller is devised to guarantee the positiveness of the closed-loop MJNNs. Moreover, some sufficient conditions for the existence of the controller gain solutions are proposed and proved by using the stochastic Lyapunov-Krasovskii functional approach and linear matrix inequalities techniques. Finally, we give two simulation examples to demonstrate the effectiveness and feasibility of the proposed methods.

论文关键词:Markovian jumping neural networks,Positiveness,Finite-time stabilizable,Stochastic Lyapunov-Krasovskii functional

论文评审过程:Received 18 April 2019, Revised 7 July 2019, Accepted 22 July 2019, Available online 7 September 2019, Version of Record 7 September 2019.

论文官网地址:https://doi.org/10.1016/j.amc.2019.124631