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Exponential synchronization for arrays of coupled neural networks with time-delay couplings

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Abstract

This paper deals with global exponential synchronization in arrays of coupled delayed neural networks with both delayed coupling and one single delayed one. Through employing Kronecker product and convex combination technique, two novel synchronization criteria are presented in terms of linear matrix inequalities (LMIs), and these conditions are dependent on the bounds of both time-delay and its derivative. Through employing Matlab LMI Toolbox and adjusting some matrix parameters in the derived results, we can realize the design and applications of the addressed systems, which shows that our methods improve and extend those reported methods. The efficiency and applicability of the proposed results can be demonstrated by three numerical examples with simulations.

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Authors and Affiliations

  1. School of Electronic Engineering and Automation, Henan Polytechnic University, Jiaozuo, 454000, Henan, China

    Tao Li

  2. School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, Jiangsu, China

    Ai-guo Song

  3. Key Laboratory of Measurement and Control of CSE (School of Automation, Southeast University), Ministry of Education, Nanjing, 210096, Jiangsu, China

    Ting Wang & Shu-min Fei

Authors
  1. Tao Li
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  2. Ting Wang
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  3. Ai-guo Song
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  4. Shu-min Fei
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Corresponding author

Correspondence to Tao Li.

Additional information

Recommended by Editorial Board member Euntai Kim under the direction of Editor Young-Hoon Joo. This work is supported by National Natural Science Foundation of China No.60835001, No.60875035, No.60904023, No.61004032, Jiangsu Planned Projects for Postdoctoral Research Fund No.0901005B, China Postdoctoral Science Foundation Funded Project No. 200904501033, Natural Science Foundation of Jiangsu No. BK2008294, Postdoctoral Key Research Fund of Southeast University, and the Open Laboratory Fund of Key Subject on Control Engineering of Henan Province No. KG2009-04.

Tao Li received his Ph.D. degree in Engineering from Southeast University in 2008 and now, he is a postdoctoral research fellow at School of Instrument Science and Engineering in Southeast University. His current research interests include neural networks, time-delay systems, networked control, etc.

Ting Wang received her master degree in Engineering from Shandong University in 2008 and now, she is a doctor candidate at School of Automation in Southeast University. Her current research interests include networked control systems and smart grid.

Ai-guo Song received his Ph.D. degree in Engineering from Southeast University in 1996. He has been a senior researcher at Northwest University in USA from 2003 to 2004 and now, he is a professor at School of Instrument Science and Engineering in Southeast University. He current research interests include robotics, signal processing and recovery robot.

Shu-min Fei received his Ph.D. degree from Beijing University of Aeronautics and Astronautics, China in 1995. Now, he is a professor and doctoral advisor at Southeast University. His current research interests include nonlinear systems, time-delay system, complex systems, and so on.

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Li, T., Wang, T., Song, Ag. et al. Exponential synchronization for arrays of coupled neural networks with time-delay couplings. Int. J. Control Autom. Syst. 9, 187–196 (2011). https://doi.org/10.1007/s12555-011-0124-4

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  • DOI: https://doi.org/10.1007/s12555-011-0124-4

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