title: Stability of delayed memristive neural networks with time-varying impulses.
abstract: This paper addresses the stability problem on the memristive neural networks with time-varying impulses. Based on the memristor theory and neural network theory, the model of the memristor-based neural network is established. Different from the most publications on memristive networks with fixed-time impulse effects, we consider the case of time-varying impulses. Both the destabilizing and stabilizing impulses exist in the model simultaneously. Through controlling the time intervals of the stabilizing and destabilizing impulses, we ensure the effect of the impulses is stabilizing. Several sufficient conditions for the globally exponentially stability of memristive neural networks with time-varying impulses are proposed. The simulation results demonstrate the effectiveness of the theoretical results.
authors.affiliation: College of Computer Science, Chongqing University, Chongqing, 400044 China.
authors.forename: Jiangtao
authors.initials: J
authors.lastname: Qi
authors.affiliation: College of Computer Science, Chongqing University, Chongqing, 400044 China.
authors.forename: Chuandong
authors.initials: C
authors.lastname: Li
authors.affiliation: Department of Mathematics, Texas A&M University at Qatar, PO Box 23874, Doha, Qatar.
authors.forename: Tingwen
authors.initials: T
authors.lastname: Huang
keywords: Exponential stability; Memristive neural networks; Time-varying delays; Time-varying impulses