Finite-Time Boundedness Analysis of Memristive Neural Network with Time-Varying Delay

摘要

This paper considers the issue of the finite-time boundedness (FTB) of memristive neural network (MNN) with time-varying delay. It is known that the parameters of MNN are state dependent, the system stability of MNN via the classical analytical techniques is not realized directly. Hence, a novel technique is first developed to transform the MNN into the form of neural network with uncertain parameters in the paper. Further by introducing the appropriate Lyapunov function and the concept of FTB, a new method is proposed to guarantee that the state trajectory remains in a bounded region of the state space over a given finite-time interval. Finally, two numerical examples are given to illustrate the effectiveness of our proposed approaches.