Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying Delays

This paper studies fractional-order neural networks with neutral-type delay, leakage delay, and time-varying delays. A sufficient condition which ensures the finite-time synchronization of these networks based on a state feedback control scheme is deduced using the generalized Gronwall–Bellman inequ...

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Main Authors: Călin-Adrian Popa, Eva Kaslik
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/8/7/1146
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author Călin-Adrian Popa
Eva Kaslik
author_facet Călin-Adrian Popa
Eva Kaslik
author_sort Călin-Adrian Popa
collection DOAJ
description This paper studies fractional-order neural networks with neutral-type delay, leakage delay, and time-varying delays. A sufficient condition which ensures the finite-time synchronization of these networks based on a state feedback control scheme is deduced using the generalized Gronwall–Bellman inequality. Then, a different state feedback control scheme is employed to realize the finite-time Mittag–Leffler synchronization of these networks by using the fractional-order extension of the Lyapunov direct method for Mittag–Leffler stability. Two numerical examples illustrate the feasibility and the effectiveness of the deduced sufficient criteria.
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spelling doaj.art-ea8d414f53264c50bf23af5c88a297332023-11-20T06:38:45ZengMDPI AGMathematics2227-73902020-07-0187114610.3390/math8071146Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying DelaysCălin-Adrian Popa0Eva Kaslik1Department of Mathematics, West University of Timişoara, Blvd. V. Pârvan, No. 4, 300223 Timişoara, RomaniaDepartment of Computer Science, West University of Timişoara, Blvd. V. Pârvan, No. 4, 300223 Timişoara, RomaniaThis paper studies fractional-order neural networks with neutral-type delay, leakage delay, and time-varying delays. A sufficient condition which ensures the finite-time synchronization of these networks based on a state feedback control scheme is deduced using the generalized Gronwall–Bellman inequality. Then, a different state feedback control scheme is employed to realize the finite-time Mittag–Leffler synchronization of these networks by using the fractional-order extension of the Lyapunov direct method for Mittag–Leffler stability. Two numerical examples illustrate the feasibility and the effectiveness of the deduced sufficient criteria.https://www.mdpi.com/2227-7390/8/7/1146fractional-order neural networksfinite-time synchronizationneutral-type neural networksleakage delayMittag–Leffler function
spellingShingle Călin-Adrian Popa
Eva Kaslik
Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying Delays
Mathematics
fractional-order neural networks
finite-time synchronization
neutral-type neural networks
leakage delay
Mittag–Leffler function
title Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying Delays
title_full Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying Delays
title_fullStr Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying Delays
title_full_unstemmed Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying Delays
title_short Finite-Time Mittag–Leffler Synchronization of Neutral-Type Fractional-Order Neural Networks with Leakage Delay and Time-Varying Delays
title_sort finite time mittag leffler synchronization of neutral type fractional order neural networks with leakage delay and time varying delays
topic fractional-order neural networks
finite-time synchronization
neutral-type neural networks
leakage delay
Mittag–Leffler function
url https://www.mdpi.com/2227-7390/8/7/1146
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