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Equilibrium Analysis for Improved Signal Range Model of Delayed Cellular Neural Networks

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Abstract

In this paper, a class of delayed cellular neural networks with unbounded activation functions and described by using space invariant cloning templates are considered. The general and explicit existing regions of equilibrium points are discussed based on dissipative theory, fixed point principle of iteration mapping and Brouwer Fixed-point Theorem. The sufficient condition is obtained to ensure the existence, uniqueness, local asymptotical stability of the equilibrium point in each saturation sub-region. Moreover, we give the condition for equilibrium point to be globally exponentially stable, and the explicit existing region of the unique equilibrium point is also located. These results extend previous works on these issues for the standard delayed cellular neural networks. Two numerical examples are given to show the validity of the obtained results.

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Authors and Affiliations

  1. Department of Mathematics, Huzhou Teacher’s College, Huzhou, Zhejiang, 313000, People’s Republic of China

    Liping Li

  2. College of Mathematics and Econometrics, Hunan University, Changsha, Hunan, 410082, People’s Republic of China

    Liping Li & Lihong Huang

Authors
  1. Liping Li
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  2. Lihong Huang
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Correspondence to Liping Li.

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Li, L., Huang, L. Equilibrium Analysis for Improved Signal Range Model of Delayed Cellular Neural Networks. Neural Process Lett 31, 177–194 (2010). https://doi.org/10.1007/s11063-010-9134-0

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  • DOI: https://doi.org/10.1007/s11063-010-9134-0

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