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On the Finite-Time Boundedness and Finite-Time Stability of Caputo-Type Fractional Order Neural Networks with Time Delay and Uncertain Terms

Authors :
Bandana Priya
Ganesh Kumar Thakur
M. Syed Ali
Gani Stamov
Ivanka Stamova
Pawan Kumar Sharma
Source :
Fractal and Fractional, Vol 6, Iss 7, p 368 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

This study investigates the problem of finite-time boundedness of a class of neural networks of Caputo fractional order with time delay and uncertain terms. New sufficient conditions are established by constructing suitable Lyapunov functionals to ensure that the addressed fractional-order uncertain neural networks are finite-time stable. Criteria for finite-time boundedness of the considered fractional-order uncertain models are also achieved. The obtained results are based on a newly developed property of Caputo fractional derivatives, properties of Mittag–Leffler functions and Laplace transforms. In addition, examples are developed to manifest the usefulness of our theoretical results.

Details

Language :
English
ISSN :
25043110
Volume :
6
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Fractal and Fractional
Publication Type :
Academic Journal
Accession number :
edsdoj.215f4ddc026a4e6896dee31ce07f9344
Document Type :
article
Full Text :
https://doi.org/10.3390/fractalfract6070368