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Existence and Attractivity of Almost Periodic Solution for Recurrent Neural Networks with Unbounded Delays and Variable Coefficients

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Abstract

This paper presents several sufficient conditions for the existence and attractivity of almost periodic solution for a new class of recurrent neural networks with unbounded delays and variable coefficients. Different from the normal approach, that's to say, without resorting to any Lyapunov function, these results are obtained by utilizing generalized Halanay inequality technique and combining the theory of exponential dichotomy with fixed point method. Some existing results are found to be special case of this paper. In addition, the exponential stability of the almost periodic solution, which is not studied in the earlier references, is also considered for the system. An example is given to illustrate the feasibility of our results.

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Authors and Affiliations

  1. Department of Mathematics, Southeast University, Nanjing, 210096, China

    Xia Huang & Jinde Cao

  2. Department of Mathematics, City University of Hong Kong, Hong Kong, China

    Daniel W. C. Ho

Authors
  1. Xia Huang
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  2. Jinde Cao
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  3. Daniel W. C. Ho
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Corresponding author

Correspondence to Jinde Cao.

Additional information

This work was jointly supported by the National Natural Science Foundation of China under Grant 60373067, the Hong Kong Special Administrative Region, China with Project No. 7001146, the Natural Science Foundation of Jiangsu Province, China under Grant BK2003053, Qing-Lan Engineering Project of Jiangsu Province, China.

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Huang, X., Cao, J. & Ho, D.W.C. Existence and Attractivity of Almost Periodic Solution for Recurrent Neural Networks with Unbounded Delays and Variable Coefficients. Nonlinear Dyn 45, 337–351 (2006). https://doi.org/10.1007/s11071-005-9011-y

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  • DOI: https://doi.org/10.1007/s11071-005-9011-y

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