title: Exponential Stability of Complex-Valued Memristive Recurrent Neural Networks.
abstract: 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.
authors.forename: Huamin
authors.initials: H
authors.lastname: Wang
authors.forename: Shukai
authors.initials: S
authors.lastname: Duan
authors.forename: Tingwen
authors.initials: T
authors.lastname: Huang
authors.forename: Lidan
authors.initials: L
authors.lastname: Wang
authors.forename: Chuandong
authors.initials: C
authors.lastname: Li