Оригинал (Original)
Автори: Стамов, Т. Г., Стамов, Г. Т., Stamova I., Господинова, Е. А.
Заглавие: Lyapunov approach to manifolds stability for impulsive Cohen–Grossberg-type conformable neural network models
Ключови думи: Cohen–Grossberg neural networks; conformable derivative; imp

Абстракт: In this paper, motivated by the advantages of the generalized conformable derivatives, an impulsive conformable Cohen–Grossberg-type neural network model is introduced. The impulses, which can be also considered as a control strategy, are at fixed instants of time. We define the notion of practical stability with respect to manifolds. A Lyapunov-based analysis is conducted, and new criteria are proposed. The case of bidirectional associative memory (BAM) network model is also investigated. Examples are given to demonstrate the effectiveness of the established results.

Библиография

    Издание

    Math. Biosci. Eng, том 20, брой 8, 2023, САЩ,
    		Autors: Stamov, T. G., Stamov, G. T., Stamova I., Gospodinova, E. A.
    Title: Lyapunov approach to manifolds stability for impulsive Cohen–Grossberg-type conformable neural network models
    Keywords: Cohen–Grossberg neural networks; conformable derivative; impulses; manifolds; practical stability

    Abstract: In this paper, motivated by the advantages of the generalized conformable derivatives, an impulsive conformable Cohen–Grossberg-type neural network model is introduced. The impulses, which can be also considered as a control strategy, are at fixed instants of time. We define the notion of practical stability with respect to manifolds. A Lyapunov-based analysis is conducted, and new criteria are proposed. The case of bidirectional associative memory (BAM) network model is also investigated. Examples are given to demonstrate the effectiveness of the established results.

    References

      Issue

      Math. Biosci. Eng, vol. 20, issue 8, 2023, United States,

      Цитирания (Citation/s):
      1. α-Synchronization of a Class of Unbounded Delayed Inertial Cohen–Grossberg Neural Networks with Delayed Impulses - 2023 - в издания, индексирани в Scopus или Web of Science

      Вид: пленарен доклад в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science