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Global Exponential Stability for Impulsive BAM Neural Networks with Distributed Delays on Time Scales

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Abstract

In this paper, by utilizing the time scale calculus theory, topological degree theory and Hölder’s inequality on time scales, we analyze a class of impulsive BAM neural networks with distributed delays on time scales. Some sufficient conditions are obtained to ensure the existence, uniqueness and the global exponential stability of the equilibrium point. Finally, an example is provided to demonstrate the effectiveness of the results.

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Authors and Affiliations

  1. Department of Mathematics, Yunnan University, 650091, Yunnan, Kunming, People’s Republic of China

    Yongkun Li & Shan Gao

Authors
  1. Yongkun Li
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  2. Shan Gao
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Corresponding author

Correspondence to Yongkun Li.

Additional information

This work is supported by the National Natural Sciences Foundation of People’s Republic of China.

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Li, Y., Gao, S. Global Exponential Stability for Impulsive BAM Neural Networks with Distributed Delays on Time Scales. Neural Process Lett 31, 65–91 (2010). https://doi.org/10.1007/s11063-009-9127-z

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  • DOI: https://doi.org/10.1007/s11063-009-9127-z

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