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**Globally exponentially robust stability and periodicity of delayed neural networks.**
*(English)*
Zbl 1061.94552

Summary: A new concept of robust periodicity is introduced, and the problem of robust stability and robust periodicity is discussed for delayed neural networks. Several sufficient conditions are derived for globally exponentially robust stability and robust periodicity of delayed neural networks based on the Lyapunov method. These results improve and extend those given in the earlier references.

### MSC:

94C05 | Analytic circuit theory |

68T05 | Learning and adaptive systems in artificial intelligence |

93D20 | Asymptotic stability in control theory |

93C10 | Nonlinear systems in control theory |

34D05 | Asymptotic properties of solutions to ordinary differential equations |

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\textit{J. Cao} and \textit{T. Chen}, Chaos Solitons Fractals 22, No. 4, 957--963 (2004; Zbl 1061.94552)

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### References:

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