Volume 8 Number 1
February 2011
Article Contents
Hong-Bing Zeng, Shen-Ping Xiao and Bin Liu. New Stability Criteria for Recurrent Neural Networks with a Time-varying Delay. International Journal of Automation and Computing, vol. 8, no. 1, pp. 128-133, 2011. doi: 10.1007/s11633-010-0564-y
Cite as: Hong-Bing Zeng, Shen-Ping Xiao and Bin Liu. New Stability Criteria for Recurrent Neural Networks with a Time-varying Delay. International Journal of Automation and Computing, vol. 8, no. 1, pp. 128-133, 2011. doi: 10.1007/s11633-010-0564-y

New Stability Criteria for Recurrent Neural Networks with a Time-varying Delay

Author Biography:
  • Shen-Ping Xiao received the B.Sc.degree in engineering from Northeastern Univer-sity,Shenyang,PRC in 1988,and Ph.D.

  • Corresponding author: Hong-Bing Zeng received the B.Sc.degree in electrical engineering from Tianjin University of Technology and Education, Tianjin,PRC in 2003,and M.Sc.
  • Received: 2009-12-09
Fund Project:

supported by National Natural Science Foundation of China (No.60874025);Natural Science Foundation of Hunan Province of China (No.10JJ6098)

通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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New Stability Criteria for Recurrent Neural Networks with a Time-varying Delay

  • Corresponding author: Hong-Bing Zeng received the B.Sc.degree in electrical engineering from Tianjin University of Technology and Education, Tianjin,PRC in 2003,and M.Sc.
Fund Project:

supported by National Natural Science Foundation of China (No.60874025);Natural Science Foundation of Hunan Province of China (No.10JJ6098)

Abstract: This paper deals with the stability of static recurrent neural networks (RNNs) with a time-varying delay. An augmented Lyapunov-Krasovskii functional is employed, in which some useful terms are included. Furthermore, the relationship among the timevarying delay, its upper bound and their difierence, is taken into account, and novel bounding techniques for 1(t) are employed. As a result, without ignoring any useful term in the derivative of the Lyapunov-Krasovskii functional, the resulting delay-dependent criteria show less conservative than the existing ones. Finally, a numerical example is given to demonstrate the effectiveness of the proposed methods.

Hong-Bing Zeng, Shen-Ping Xiao and Bin Liu. New Stability Criteria for Recurrent Neural Networks with a Time-varying Delay. International Journal of Automation and Computing, vol. 8, no. 1, pp. 128-133, 2011. doi: 10.1007/s11633-010-0564-y
Citation: Hong-Bing Zeng, Shen-Ping Xiao and Bin Liu. New Stability Criteria for Recurrent Neural Networks with a Time-varying Delay. International Journal of Automation and Computing, vol. 8, no. 1, pp. 128-133, 2011. doi: 10.1007/s11633-010-0564-y
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