Exponential Stability of Switched Time-varying Delayed Neural Networks with All Modes Being Unstable

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• 作者：Jiangtao Qi ; Chuandong Li ; Tingwen Huang ; Wei Zhang
• 关键词：Exponential stability ; Neural network ; Unstable subsystem ; Time ; varying delay ; Dwell time ; Comparison principle ; Discretized Lyapunov function
• 刊名：Neural Processing Letters
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：43
• 期：2
• 页码：553-565
• 全文大小：544 KB
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• 作者单位：Jiangtao Qi (1)
  Chuandong Li (1)
  Tingwen Huang (2)
  Wei Zhang (1)
  
  1. College of Computer Science, Chongqing University, Chongqing, 400044, China
  2. Texas A & M University at Qatar, Doha, 5825, Qatar
  
• 刊物类别：Physics and Astronomy
• 刊物主题：Physics
  Complexity
  Artificial Intelligence and Robotics
  Electronic and Computer Engineering
  Operation Research and Decision Theory
  
• 出版者：Springer Netherlands
• ISSN：1573-773X

文摘

This paper aims to design an appropriate switching law to stabilize the switched neural networks with time-varying delays when all subsystems are unstable. By using the discretized Lyapunov function approach and the extended comparison principle for impulsive systems, the stability of switched delayed neural networks composed full of unstable subsystems is analyzed and a computable sufficient condition is derived in the framework of dwell time. The effectiveness of the proposed results is illustrated by a numerical example.