On Exponential Periodicity And Stability of Nonlinear Neural Networks With Variable Coefficients And Distributed Delays

Authors

  • Xuyang Lou Research Center of Control Science and Engineering, Jiangnan University, 1800 Lihu Rd.,Wuxi, Jiangsu 214122, P.R.China
  • Baotong Cui Research Center of Control Science and Engineering, Jiangnan University, 1800 Lihu Rd.,Wuxi, Jiangsu 214122, P.R.China

Keywords:

Neural networks, Exponential periodicity, Distributed delays, Young inequality

Abstract

The exponential periodicity and stability of continuous nonlinear neural networks with variable coefficients and distributed delays are investigated via employing Young inequality technique and Lyapunov method. Some new sufficient conditions ensuring existence and uniqueness of periodic solution for a general class of neural systems are obtained. Without assuming the activation functions are to be bounded, differentiable or strictly increasing. Moreover, the symmetry of the connection matrix is not also necessary. Thus, we generalize and improve some previous works, and they are easy to check and apply in practice.

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References

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Published

2007-10-01

How to Cite

Lou, X., & Cui, B. (2007). On Exponential Periodicity And Stability of Nonlinear Neural Networks With Variable Coefficients And Distributed Delays. Journal of Computer Science and Technology, 7(03), p. 235–242. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/776

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Original Articles