Exponential Stabilization of Time‐varying Delayed Complex‐valued Memristor‐based Neural Networks Via Impulsive Control

Abstract

The exponential stabilization problem for a class of time-varying delayed complex-valued memristor-based neural networks via discontinuous impulsive control is investigated in this paper. Firstly, the time-varying delayed complex-valued memristor-based neural networks is translated to real-valued memristor-based neural networks. Secondly, an impulsive control law is constructed to guarantee exponential stabilization of the complex-valued memristor-based neural networks with time-varying delays. Thirdly, by constructing an appropriate Lyapunov Krasovskii functional and adopting linear matrix inequality (LMI) technique, some sufficient exponential stabilization criteria are derived. Finally, an illustrative example is provided to illustrate the effectiveness of the obtained theoretical results.

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