Novel Switching Jumps Dependent Exponential Synchronization Criteria for Memristor-Based Neural Networks

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• 作者：Sanbo Ding ; Zhanshan Wang ; Zhanjun Huang ; Huaguang Zhang
• 关键词：Memristor ; based neural networks ; Synchronization control ; Switching jumps
• 刊名：Neural Processing Letters
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：45
• 期：1
• 页码：15-28
• 全文大小：
• 刊物类别：Physics and Astronomy
• 刊物主题：Artificial Intelligence (incl. Robotics); Complex Systems; Computational Intelligence;
• 出版者：Springer US
• ISSN：1573-773X
• 卷排序：45

文摘

This paper investigates the problem of global exponential synchronization for memristor-based neural networks with delay. Based on the nonsmooth analysis and differential inclusion theory, a new analytic technique is employed to design a discontinuous state feedback controller, which ensures the memristor-based drive system exponential synchronize with the response system. The succinct synchronization conditions is closely relate to the switching jumps. The estimated rate of the exponential synchronization can be obtained by solving a sample algebra equation. Simulation results are given to show the effectiveness and benefits of the proposed methods.