Stability of a Class of Fractional-Order Neutral Time-Delay Neural Networks

本文考虑了一类具有时变时滞的分数阶中立型神经网络模型。根据同胚映射原理证明了该系统平衡点的存在唯一性。然后通过构造Lyapunov泛函以及利用Lyapunov稳定性理论,证明了系统渐近稳定的充分条件。In this paper, a class of fractional-order neutral neural network models with time-varying delays was considered. The uniqueness of the existence of the equilibrium point of the system is proved by the principle of homeomorphic mapping. Then, by constructing Lyapunov functional and using Lyapunov stability theory, the sufficient conditions for asymptotic stability of the system are proved.

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Publication Details

Journal
Pure Mathematics
Published
2025-01-01
DOI
https://doi.org/10.12677/pm.2025.151007
Primary Topic
Neural Networks and Applications
Type
article
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article

Stability of a Class of Fractional-Order Neutral Time-Delay Neural Networks

行 曹
Pure Mathematics
Neural Networks and Applications
article

Stability of a Class of Fractional-Order Neutral Time-Delay Neural Networks

行 曹
article en

Abstract

本文考虑了一类具有时变时滞的分数阶中立型神经网络模型。根据同胚映射原理证明了该系统平衡点的存在唯一性。然后通过构造Lyapunov泛函以及利用Lyapunov稳定性理论,证明了系统渐近稳定的充分条件。In this paper, a class of fractional-order neutral neural network models with time-varying delays was considered. The uniqueness of the existence of the equilibrium point of the system is proved by the principle of homeomorphic mapping. Then, by constructing Lyapunov functional and using Lyapunov stability theory, the sufficient conditions for asymptotic stability of the system are proved.

Pure MathematicsVol. 15(01)
Openalex Percentile: Top 100%
Neural Networks and Applications
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Stability of a Class of Fractional-Order Neutral Time-Delay Neural Networks — 行 曹 · Pure Mathematics (2025) | TGRS Research Map | TGRS