Improved Quasiuniform Stability for Fractional Order Neural Nets with Mixed Delay

Naifar Omar; Jmal Assaad; Nagy A. M.Ben Makhlouf Abdellatif

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Improved Quasiuniform Stability for Fractional Order Neural Nets with Mixed Delay

机译：Improved Quasiuniform Stability for Fractional Order Neural Nets with Mixed Delay

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摘要

In the present paper, a quasiuniform stability result for fractional order neural networks with mixed delay is developed, based on the generalized Gronwall inequality and the Caputo fractional derivative. Sufficient conditions are derived to ensure the quasiuniform stability of the considered neural nets system. A clarification example is carried out not only to validate the authors' theoretical results but also to show the superiority of the developed work (in terms of improved stability), compared with other similar works already published in the literature.

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《Mathematical Problems in Engineering: Theory, Methods and Applications》 |2020年第43期|8811226.1-8811226.7|共7页
作者
Naifar Omar; Jmal Assaad; Nagy A. M.Ben Makhlouf Abdellatif;
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Sfax Univ, Natl Sch Engn, Control & Energy Management Lab, BP 1173, Sfax 3038, Tunisia;

Benha Univ, Dept Math, Fac Sci, Banha 13518, Egypt|Kuwait Univ, Safat, Kuwait;

Jouf Univ, Aljouf, Saudi Arabia|Univ Sfax, Sci Fac, Math Dept, Sfax, Tunisia;

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Improved Quasiuniform Stability for Fractional Order Neural Nets with Mixed Delay

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