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Exponential stability of stochastic high-order BAM neural networks with time delays and impulsive effects

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Abstract

In this paper, we consider the problem on exponential stability analysis of the stochastic impulsive high-order BAM neural networks with time delays. Through employing Lyapunov function method and stochastic bidirected halanay inequality, we constitute exponential stability of the stochastic impulsive high-order BAM neural networks with its estimated exponential convergence rate and feasible interval of impulsive strength. An example illustrates the main results.

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Authors and Affiliations

  1. College of Resource and Environmental Science, Chongqing University, Chongqing, China

    Danjie Lu

  2. School of Science, Information Technology and Engineering, University of Ballarat, Ballarat, VIC, Australia

    Chaojie Li

Authors
  1. Danjie Lu
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  2. Chaojie Li
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Correspondence to Chaojie Li.

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Lu, D., Li, C. Exponential stability of stochastic high-order BAM neural networks with time delays and impulsive effects. Neural Comput & Applic 23, 1–8 (2013). https://doi.org/10.1007/s00521-012-0861-1

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  • DOI: https://doi.org/10.1007/s00521-012-0861-1

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