Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Cybernetics

, volume 50 , issue 6 , pages 2758-2769

Anti-Synchronization in Fixed Time for Discontinuous Reaction–Diffusion Neural Networks With Time-Varying Coefficients and Time Delay

Zengyun Wang ^{1, 2}

Ahmed Alsaedi ^{1, 3}

Zuowei Cai ⁴

Leszek Rutkowski ^{5, 6}

Hide authors affiliations Show authors affiliations: 6 affiliations

School of Mathematics, Southeast University, Nanjing, China |

School of Mathematics and Computational Science, Hunan First Normal University, Changsha, China |

Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Southeast University, Nanjing, China |

⁴

Department of Technology, Hunan Women’s University, Changsha, China |

⁵

Institute of Computational Intelligence, Częstochowa University of Technology, Częstochowa, Poland |

⁶

Information Technology Institute, University of Social Sciences, Łódź, Poland |

Publication type: Journal Article

Publication date: 2020-06-01

Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Cybernetics

scimago Q1

wos Q1

SJR: 4.450

CiteScore: 25.7

Impact factor: 10.5

ISSN: 21682267, 21682275

DOI: 10.1109/tcyb.2019.2913200

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PubMed ID: 31095503

Computer Science Applications

Electrical and Electronic Engineering

Information Systems

Software

Control and Systems Engineering

Human-Computer Interaction

Abstract

This paper studies the fixed-time anti-synchronization (FTAS) of discontinuous reaction-diffusion neural networks (DRDNNs) with both time-varying coefficients and time delay. First, differential inclusion theory is used to deal with the influence caused by discontinuous activations. In addition, a new fixed-time convergence theorem is used to handle the time-varying coefficients. Second, a novel state-feedback control algorithm and integral state-feedback control algorithm are proposed to realize FTAS of DRDNNs. During the generalized (adaptive) pinning control strategy, a guideline is proposed to select neurons to pin the designed controller. Furthermore, we present several criteria on FTAS by using the generalized Lyapunov function method. Different from the traditional Lyapunov function with negative definite derivative, the derivative of the Lyapunov function can be positive in this paper. Finally, we give two numerical simulations to substantiate the merits of the obtained results.

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GOST |

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Wang Z. et al. Anti-Synchronization in Fixed Time for Discontinuous Reaction–Diffusion Neural Networks With Time-Varying Coefficients and Time Delay // IEEE Transactions on Cybernetics. 2020. Vol. 50. No. 6. pp. 2758-2769.

GOST all authors (up to 50) Copy

Wang Z., Alsaedi A., Cai Z., Rutkowski L. Anti-Synchronization in Fixed Time for Discontinuous Reaction–Diffusion Neural Networks With Time-Varying Coefficients and Time Delay // IEEE Transactions on Cybernetics. 2020. Vol. 50. No. 6. pp. 2758-2769.

RIS |

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RIS Copy

TY - JOUR

DO - 10.1109/tcyb.2019.2913200

UR - https://doi.org/10.1109/tcyb.2019.2913200

TI - Anti-Synchronization in Fixed Time for Discontinuous Reaction–Diffusion Neural Networks With Time-Varying Coefficients and Time Delay

T2 - IEEE Transactions on Cybernetics

AU - Wang, Zengyun

AU - Alsaedi, Ahmed

AU - Cai, Zuowei

AU - Rutkowski, Leszek

PY - 2020

DA - 2020/06/01

PB - Institute of Electrical and Electronics Engineers (IEEE)

SP - 2758-2769

IS - 6

VL - 50

PMID - 31095503

SN - 2168-2267

SN - 2168-2275

ER -

BibTex |

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BibTex (up to 50 authors) Copy

@article{2020_Wang,

author = {Zengyun Wang and Ahmed Alsaedi and Zuowei Cai and Leszek Rutkowski},

title = {Anti-Synchronization in Fixed Time for Discontinuous Reaction–Diffusion Neural Networks With Time-Varying Coefficients and Time Delay},

journal = {IEEE Transactions on Cybernetics},

year = {2020},

volume = {50},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

month = {jun},

url = {https://doi.org/10.1109/tcyb.2019.2913200},

number = {6},

pages = {2758--2769},

doi = {10.1109/tcyb.2019.2913200}

}

MLA

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MLA Copy

Wang, Zengyun, et al. “Anti-Synchronization in Fixed Time for Discontinuous Reaction–Diffusion Neural Networks With Time-Varying Coefficients and Time Delay.” IEEE Transactions on Cybernetics, vol. 50, no. 6, Jun. 2020, pp. 2758-2769. https://doi.org/10.1109/tcyb.2019.2913200.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Journal

IEEE Transactions on Cybernetics

scimago Q1

wos Q1

SJR

4.450

CiteScore

25.7

Impact factor

10.5

ISSN

21682267 (Print)

21682275 (Electronic)