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Dissipativity analysis of neural networks with time-varying delays

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Abstract

A new definition of dissipativity for neural networks is presented in this paper. By constructing proper Lyapunov functionals and using some analytic techniques, sufficient conditions are given to ensure the dissipativity of neural networks with or without time-varying parametric uncertainties and the integro-differential neural networks in terms of linear matrix inequalities. Numerical examples are given to illustrate the effectiveness of the obtained results.

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Authors and Affiliations

  1. School of Communication and Control Engineering, Jiangnan University, Wuxi, Jiangsu, 214122, PRC

    Yan Sun & Bao-Tong Cui

Authors
  1. Yan Sun
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  2. Bao-Tong Cui
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Correspondence to Bao-Tong Cui.

Additional information

This work was supported by National Natural Science Foundation of China (No. 60674026), Key Project of Chinese Ministry of Education (No. 107058), Jiangsu Provincial Natural Science Foundation of China (No. BK2007016).

Yan Sun received the B. Sc. degree from Zhengzhou University, PRC, in 2005. She is now a master student in the School of Communication and Control Engineering, Jiangnan University, PRC.

Her research interests include dissipative control and energy decoupling.

Bao-Tong Cui received the Ph.D. degree in control theory and control engineering from the College of Automation Science and Engineering, South China University of Technology, PRC, in July 2003. He was a post-doctoral fellow at Shanghai Jiaotong University, PRC, from July 2003 to September 2005, and a visiting scholar at Department of Electrical and Computer Engineering, National University of Singapore from August 2007 to February 2008. He became an associate professor in December 1993 and a professor in November 1995 at Department of Mathematics, Binzhou University, Shandong, PRC. He joined the School of Communication and Control Engineering, Jiangnan University, PRC, in June 2003, where he is a professor.

His research interests include systems analysis, stability theory, impulsive control, artificial neural networks, and chaos synchronization.

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Sun, Y., Cui, BT. Dissipativity analysis of neural networks with time-varying delays. Int. J. Autom. Comput. 5, 290–295 (2008). https://doi.org/10.1007/s11633-008-0290-x

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  • DOI: https://doi.org/10.1007/s11633-008-0290-x

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