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The multiple \(\mu \) -stability of delayed state-dependent switching neural networks is studied in this article, where the activation functions are discontinuous, piecewise and nonlinear. Based on Brouwer’s Fixed Point Theorem, several conditions are derived to guarantee the networks have \(6^{n}\) equilibrium points, \(4^{n}\) of which are locally \(\mu \) -stable. Finally, with one numerical simulation, the validity of the theoretical analysis is shown.

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Multiple \(\mu \) -Stability of Delayed State-Dependent Switching Neural Networks With Discontinuous Activation Function

  • 会议论文

  • 发表日期：

    2026年

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  • Manchun Tan,
  • Weihao Du

摘要

The multiple \(\mu \) -stability of delayed state-dependent switching neural networks is studied in this article, where the activation functions are discontinuous, piecewise and nonlinear. Based on Brouwer’s Fixed Point Theorem, several conditions are derived to guarantee the networks have \(6^{n}\) equilibrium points, \(4^{n}\) of which are locally \(\mu \) -stable. Finally, with one numerical simulation, the validity of the theoretical analysis is shown.