Exponential Stability of Complex-Valued Memristive Recurrent Neural Networks
Huamin Wang, Shukai Duan, Tingwen Huang, Lidan Wang, Chuandong Li · IEEE Transactions on Neural Networks and Learning Systems · 2016
In this brief, we establish a novel complex-valued memristive recurrent neural network (CVMRNN) to study its stability. As a generalization of real-valued memristive neural networks, CVMRNN can be separated into real and imaginary parts. By means of M -matrix and Lyapunov function, the existence, uniqueness, and exponential stability of the equilibrium point for CVMRNNs are investigated, and sufficient conditions are presented. Finally, the effectiveness of obtained results is illustrated by two numerical examples.