数学季刊 ›› 2010, Vol. 25 ›› Issue (1): 124-131.

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具扇形非线性时滞神经网络全局同步

  

  1. Department of Mathematics, Shaoguan University
  • 收稿日期:2007-12-25 出版日期:2010-03-30 发布日期:2023-06-13
  • 作者简介:HUANG You-liang(1969- ), male, native of Shixing, Guangdong, a lecturer of Shaoguan University, M.S.D., engages in the research of dynamical system and the teaching research of mathematics.

Synchronization of a Class of Delayed Neural Networks with Sector Nonlinearity 

  1. Department of Mathematics, Shaoguan University

  • Received:2007-12-25 Online:2010-03-30 Published:2023-06-13
  • About author:HUANG You-liang(1969- ), male, native of Shixing, Guangdong, a lecturer of Shaoguan University, M.S.D., engages in the research of dynamical system and the teaching research of mathematics.

摘要: In this paper, global synchronization is discussed for a general class of delayed neural networks with time-varying and distributed delays. Furthermore, the activation functions in the neural networks can be different type. Based on the drive-response concept and the Lyapunov stability theorem, some sufficient criteria are obtained to guarantee the global synchronization of the considered models even when input sector nonlinearity caused by physical limitations is presented in response systems. Finally, a typical example is also given to illustrate the effectiveness of the proposed synchronization scheme. 

关键词:  synchronization, neural networks, distributed delays, sector nonlinearity

Abstract: In this paper, global synchronization is discussed for a general class of delayed neural networks with time-varying and distributed delays. Furthermore, the activation functions in the neural networks can be different type. Based on the drive-response concept and the Lyapunov stability theorem, some sufficient criteria are obtained to guarantee the global synchronization of the considered models even when input sector nonlinearity caused by physical limitations is presented in response systems. Finally, a typical example is also given to illustrate the effectiveness of the proposed synchronization scheme. 

Key words:  synchronization, neural networks, distributed delays, sector nonlinearity

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