Volume 7 Number 2
May 2010
Article Contents
Yuan-Yuan Wu, Tao Li and Yu-Qiang Wu. Improved Exponential Stability Criteria for Recurrent Neural Networks with Time-varying Discrete and Distributed Delays. International Journal of Automation and Computing, vol. 7, no. 2, pp. 199-204, 2010. doi: 10.1007/s11633-010-0199-z
Cite as: Yuan-Yuan Wu, Tao Li and Yu-Qiang Wu. Improved Exponential Stability Criteria for Recurrent Neural Networks with Time-varying Discrete and Distributed Delays. International Journal of Automation and Computing, vol. 7, no. 2, pp. 199-204, 2010. doi: 10.1007/s11633-010-0199-z

Improved Exponential Stability Criteria for Recurrent Neural Networks with Time-varying Discrete and Distributed Delays

Author Biography:
  • Yuan-Yuan Wu received her B.Sc.and M.Sc.degrees from the College of Mathematics and Information at Henan Normal University,Xinxiang,PRC in 2003 and 2006,respectivelyd

  • Corresponding author: Yu-Qiang Wu received the Ph.D.degree in automatic control from Southeast University,Nanjing,PRC in 1994
  • Received: 2008-10-23
Fund Project:

supported by National Natural Science Foundation of China (No.60674027,No.60974127);Key Project of Education Ministry of China (No.208074)

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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Improved Exponential Stability Criteria for Recurrent Neural Networks with Time-varying Discrete and Distributed Delays

  • Corresponding author: Yu-Qiang Wu received the Ph.D.degree in automatic control from Southeast University,Nanjing,PRC in 1994
Fund Project:

supported by National Natural Science Foundation of China (No.60674027,No.60974127);Key Project of Education Ministry of China (No.208074)

Abstract: In this paper, the problem of the global exponential stability analysis is investigated for a class of recurrent neural networks (RNNs) with time-varying discrete and distributed delays. Due to a novel technique when estimating the upper bound of the derivative of Lyapunov functional, we establish new exponential stability criteria in terms of LMIs. It is shown that the obtained criteria can provide less conservative results than some existing ones. Numerical examples are given to show the effectiveness of the proposed results.

Yuan-Yuan Wu, Tao Li and Yu-Qiang Wu. Improved Exponential Stability Criteria for Recurrent Neural Networks with Time-varying Discrete and Distributed Delays. International Journal of Automation and Computing, vol. 7, no. 2, pp. 199-204, 2010. doi: 10.1007/s11633-010-0199-z
Citation: Yuan-Yuan Wu, Tao Li and Yu-Qiang Wu. Improved Exponential Stability Criteria for Recurrent Neural Networks with Time-varying Discrete and Distributed Delays. International Journal of Automation and Computing, vol. 7, no. 2, pp. 199-204, 2010. doi: 10.1007/s11633-010-0199-z
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