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作者:

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

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摘要:

As multi-gene networks transmit signals and products by synchronous cooperation, investigating the synchronization of gene regulatory networks may help us to explore the biological rhythm and internal mechanisms at molecular and cellular levels. We aim to induce a type of fractional-order gene regulatory networks to synchronize at finite-time point by designing feedback controls. Firstly, a unique equilibrium point of the network is proved by applying the principle of contraction mapping. Secondly, some sufficient conditions for finite-time synchronization of fractional-order gene regulatory networks with time delay are explored based on two kinds of different control techniques and fractional Lyapunov function approach, and the corresponding setting time is estimated. Finally, some numerical examples are given to demonstrate the effectiveness of the theoretical results. (c) 2020 Elsevier Ltd. All rights reserved.

关键词:

Feedback control Finite-time synchronization Fractional-order Gene regulatory networks

作者机构:

  • [ 1 ] [Qiao, Yuanhua]Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
  • [ 2 ] [Yan, Hongyun]Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
  • [ 3 ] [Duan, Lijuan]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 4 ] [Duan, Lijuan]Beijing Key Lab Trusted Comp, Beijing 100124, Peoples R China
  • [ 5 ] [Duan, Lijuan]Natl Engn Lab Key Technol Informat Secur Level Pr, Beijing 100124, Peoples R China
  • [ 6 ] [Miao, Jun]Beijing Informat Sci & Technol Univ, Sch Comp Sci, Beijing 100101, Peoples R China

通讯作者信息:

  • 段立娟

    [Duan, Lijuan]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China;;[Duan, Lijuan]Beijing Key Lab Trusted Comp, Beijing 100124, Peoples R China;;[Duan, Lijuan]Natl Engn Lab Key Technol Informat Secur Level Pr, Beijing 100124, Peoples R China

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来源 :

NEURAL NETWORKS

ISSN: 0893-6080

年份: 2020

卷: 126

页码: 1-10

7 . 8 0 0

JCR@2022

ESI学科: COMPUTER SCIENCE;

ESI高被引阀值:34

JCR分区:1

被引次数:

WoS核心集被引频次: 53

SCOPUS被引频次: 57

ESI高被引论文在榜: 0 展开所有

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