Mittag-Leffler Synchronization of Delayed Fractional Memristor Neural Networks via Adaptive Control

Yonggui Kao; Ying Li; Ju H. Park; Xiangyong Chen

doi:10.1109/TNNLS.2020.2995718

Mittag-Leffler Synchronization of Delayed Fractional Memristor Neural Networks via Adaptive Control

Yonggui Kao
, Ying Li
, Ju H. Park^*
, Xiangyong Chen

^*Corresponding author for this work

Harbin Institute of Technology Weihai
Linyi University
Yeungnam University

Research output: Contribution to journal › Article › peer-review

119 Scopus citations

Abstract

This brief is devoted to exploring the global Mittag-Leffler (ML) synchronization problem of fractional-order memristor neural networks (FOMNNs) with leakage delay via a hybrid adaptive controller. By applying Fillipov's theory and the Lyapunov functional method, the novel algebraic sufficient condition for the global ML synchronization of FOMNNs is derived. Finally, a simulation example is presented to show the practicability of our findings.

Original language	English
Article number	9104892
Pages (from-to)	2279-2284
Number of pages	6
Journal	IEEE Transactions on Neural Networks and Learning Systems
Volume	32
Issue number	5
DOIs	https://doi.org/10.1109/TNNLS.2020.2995718
State	Published - May 2021
Externally published	Yes

Keywords

Adaptive control
Mittag-Leffler (ML) synchronization
fractional-order (FO) networks
memristor neural networks (NNs)

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10.1109/TNNLS.2020.2995718

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title = "Mittag-Leffler Synchronization of Delayed Fractional Memristor Neural Networks via Adaptive Control",

abstract = "This brief is devoted to exploring the global Mittag-Leffler (ML) synchronization problem of fractional-order memristor neural networks (FOMNNs) with leakage delay via a hybrid adaptive controller. By applying Fillipov's theory and the Lyapunov functional method, the novel algebraic sufficient condition for the global ML synchronization of FOMNNs is derived. Finally, a simulation example is presented to show the practicability of our findings.",

keywords = "Adaptive control, Mittag-Leffler (ML) synchronization, fractional-order (FO) networks, memristor neural networks (NNs)",

author = "Yonggui Kao and Ying Li and Park, \{Ju H.\} and Xiangyong Chen",

note = "Publisher Copyright: {\textcopyright} 2012 IEEE.",

year = "2021",

month = may,

doi = "10.1109/TNNLS.2020.2995718",

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AU - Kao, Yonggui

AU - Li, Ying

AU - Park, Ju H.

AU - Chen, Xiangyong

PY - 2021/5

Y1 - 2021/5

N2 - This brief is devoted to exploring the global Mittag-Leffler (ML) synchronization problem of fractional-order memristor neural networks (FOMNNs) with leakage delay via a hybrid adaptive controller. By applying Fillipov's theory and the Lyapunov functional method, the novel algebraic sufficient condition for the global ML synchronization of FOMNNs is derived. Finally, a simulation example is presented to show the practicability of our findings.

AB - This brief is devoted to exploring the global Mittag-Leffler (ML) synchronization problem of fractional-order memristor neural networks (FOMNNs) with leakage delay via a hybrid adaptive controller. By applying Fillipov's theory and the Lyapunov functional method, the novel algebraic sufficient condition for the global ML synchronization of FOMNNs is derived. Finally, a simulation example is presented to show the practicability of our findings.

KW - Adaptive control

KW - Mittag-Leffler (ML) synchronization

KW - fractional-order (FO) networks

KW - memristor neural networks (NNs)

UR - https://www.scopus.com/pages/publications/85104057026

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SN - 2162-237X

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JO - IEEE Transactions on Neural Networks and Learning Systems

JF - IEEE Transactions on Neural Networks and Learning Systems

IS - 5

M1 - 9104892

ER -

Mittag-Leffler Synchronization of Delayed Fractional Memristor Neural Networks via Adaptive Control

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Keywords

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