Dynamic behaviors of memristor-based delayed recurrent networks

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• 作者：Shiping Wen (1) (2)
  Zhigang Zeng (1) (2)
  Tingwen Huang (3)
  
• 关键词：Memristor ; Recurrent networks ; Time delays
• 刊名：Neural Computing & Applications
• 出版年：2013
• 出版时间：September 2013
• 年：2013
• 卷：23
• 期：3-4
• 页码：815-821
• 全文大小：478KB
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• 作者单位：Shiping Wen (1) (2)
  Zhigang Zeng (1) (2)
  Tingwen Huang (3)
  
  1. Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China
  2. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan, 430074, China
  3. Texas A&M University at Qatar, Doha, 5825, Qatar
  
• ISSN：1433-3058

文摘

This paper investigates the problem of the existence and global exponential stability of the periodic solution of memristor-based delayed network. Based on the knowledge of memristor and recurrent neural network, the model of the memristor-based recurrent networks is established. Several sufficient conditions are obtained, which ensure the existence of periodic solutions and global exponential stability of the memristor-based delayed recurrent networks. These results ensure global exponential stability of memristor-based network in the sense of Filippov solutions. And, it is convenient to estimate the exponential convergence rates of this network by the results. An illustrative example is given to show the effectiveness of the theoretical results.