Paper Publications

Global exponential stability for switched memristive neural networks with time-varying delays

Release time:2023-10-19  Hits:

Key Words:Memristive neural networks; Switched system; Average dwell time; Exponential stability; Linear matrix inequalities

Abstract:This paper considers the problem of exponential stability for switched memristive neural networks (MNNs) with time-varying delays. Different from most of the existing papers, we model a memristor as a continuous system, and view switched MNNs as switched neural networks with uncertain time-varying parameters. Based on average dwell time technique, mode-dependent average dwell time technique and multiple Lyapunov-Krasovskii functional approach, two conditions are derived to design the switching signal and guarantee the exponential stability of the considered neural networks, which are delay-dependent and formulated by linear matrix inequalities (LMIs). Finally, the effectiveness of the theoretical results is demonstrated by two numerical examples. (C) 2016 Elsevier Ltd. All rights reserved.

Volume:80

Issue:

Translation or Not:no