Almost Periodic Solutions of Cohen-Grossberg Neural Networks with Time-Varying Delay and Variable Impulsive Perturbations

Abstract

In this paper, we consider the problem of existence of almost periodic solutions of impulsive Cohen-Grossberg neural networks with time-varying delays. The impulses are not at fixed moments, but are realized when the integral curves of solutions meet given hypersurfaces, i.e., the investigated model is with variable impulsive perturbations. Sufficient conditions for perfect stability of almost periodic solutions are derived. The main results are obtained by employing the Lyapunov-Razumikhin method and a comparison principle. In addition, the obtained results are extended to the uncertain case, and robust stability of almost periodic solutions is also investigated. An example is considered to demonstrate the effectiveness of our results.

Department(s)

Mathematics and Statistics

Keywords and Phrases

Almost periodic functions; Cohen-Grossberg neural networks; Lyapunov'Razumikhin method; Perfect stability; Uncertain terms; Variable impulsive perturbations

International Standard Serial Number (ISSN)

1007-5704

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2020 Elsevier B.V., All rights reserved.

Publication Date

01 Jan 2020

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