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Author:

Yan, Hongyun (Yan, Hongyun.) | Qiao, Yuanhua (Qiao, Yuanhua.) (Scholars:乔元华) | Duan, Lijuan (Duan, Lijuan.) | Miao, Jun (Miao, Jun.)

Indexed by:

EI Scopus SCIE

Abstract:

In order to overcome the complexity of the theoretical analysis caused by using decomposition method to explore the finite-time synchronization behavior of fractional-order quaternion-valued neural networks (FOQVNNs), we aim to deal with this problem directly instead of decomposition. Firstly, two inequalities about quaternion are developed to broaden the current achievements in quaternion field. Secondly, a fractional differential inequality is established by using Laplace transform and applying the definition of Mittag-Leffler function. Then, by employing the presented inequalities and two different quaternion control strategies, some new conditions are derived to guarantee the finite-time synchronization of the delayed FOQVNNs. Finally, two numerical examples are given to illustrate the correctness of the main results.

Keyword:

Inequalities Fractional-order Quaternion-valued neural networks Control Finite-time synchronization

Author Community:

  • [ 1 ] [Yan, Hongyun]Beijing Univ Technol, Fac Sci, Beijing 100124, Peoples R China
  • [ 2 ] [Qiao, Yuanhua]Beijing Univ Technol, Fac Sci, Beijing 100124, Peoples R China
  • [ 3 ] [Duan, Lijuan]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 4 ] [Miao, Jun]Beijing Informat Sci & Technol Univ, Sch Comp Sci, Beijing 100101, Peoples R China

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Source :

NEURAL COMPUTING & APPLICATIONS

ISSN: 0941-0643

Year: 2022

Issue: 12

Volume: 34

Page: 9919-9930

6 . 0

JCR@2022

6 . 0 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:49

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 19

SCOPUS Cited Count: 21

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 28

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