title: Dissipativity Analysis for Stochastic Memristive Neural Networks With Time-Varying Delays: A Discrete-Time Case.
abstract: In this paper, the dissipativity problem of discrete-time memristive neural networks (DMNNs) with time-varying delays and stochastic perturbation is investigated. A class of logical switched functions are put forward to reflect the memristor-based switched property of connection weights, and the DMNNs are then recast into a tractable model. Based on the tractable model, the robust analysis method and Refined Jensen-based inequalities are applied to establish some sufficient conditions that ensure the of DMNNs. Two numerical examples are presented to illustrate the effectiveness of the obtained results.
authors.forename: Sanbo
authors.initials: S
authors.lastname: Ding
authors.forename: Zhanshan
authors.initials: Z
authors.lastname: Wang
authors.forename: Huaguang
authors.initials: H
authors.lastname: Zhang