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Almost Periodic Dynamics of a Class of Delayed Neural Networks with Discontinuous Activations

机译:一类具有不连续激活的时滞神经网络的概周期动力学

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摘要

We use the concept of the Filippov solution to study the dynamics of a class of delayed dynamical systems with discontinuous right-hand side, which contains the widely studied delayed neural network models with almost periodic self-inhibitions, interconnection weights, and external inputs. We prove that diagonal-dominant conditions can guarantee the existence and uniqueness of an almost periodic solution, as well as its global exponential stability. As special cases, we derive a series of results on the dynamics of delayed dynamical systems with discontinuous activations and periodic coefficients or constant coefficients, respectively. From the proof of the existence and uniqueness of the solution, we prove that the solution of a delayed dynamical system with high-slope activations approximates to the Filippov solution of the dynamical system with discontinuous activations.
机译:我们使用Filippov解决方案的概念来研究一类具有不连续右侧的时滞动力系统的动力学,该系统包含广泛研究的时延神经网络模型,具有几乎周期性的自我约束,互连权重和外部输入。我们证明对角占优条件可以保证几乎周期解的存在性和唯一性,以及它的全局指数稳定性。作为特殊情况,我们分别获得了具有不连续激活和周期系数或常数系数的时滞动力系统动力学的一系列结果。从解的存在性和唯一性证明,我们证明了具有高边坡激活的时滞动力系统的解近似于具有不连续激活的动力系统的Filippov解。

著录项

  • 来源
    《Neural computation》 |2008年第4期|1065-1090|共26页
  • 作者

    Wenlian Lu; Tianping Chen;

  • 作者单位
  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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