IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i13p2355-d856191.html
   My bibliography  Save this article

Impulsive Memristive Cohen–Grossberg Neural Networks Modeled by Short Term Generalized Proportional Caputo Fractional Derivative and Synchronization Analysis

Author

Listed:
  • Ravi Agarwal

    (Department of Mathematics, Texas A&M University-Kingsville, Kingsville, TX 78363, USA)

  • Snezhana Hristova

    (Faculty of Mathematics and Informatics, University of Plovdiv, Tzar Asen 24, 4000 Plovdiv, Bulgaria)

Abstract

The synchronization problem for impulsive fractional-order Cohen–Grossberg neural networks with generalized proportional Caputo fractional derivatives with changeable lower limit at any point of impulse is studied. We consider the cases when the control input is acting continuously as well as when it is acting instantaneously at the impulsive times. We defined the global Mittag–Leffler synchronization as a generalization of exponential synchronization. We obtained some sufficient conditions for Mittag–Leffler synchronization. Our results are illustrated with examples.

Suggested Citation

  • Ravi Agarwal & Snezhana Hristova, 2022. "Impulsive Memristive Cohen–Grossberg Neural Networks Modeled by Short Term Generalized Proportional Caputo Fractional Derivative and Synchronization Analysis," Mathematics, MDPI, vol. 10(13), pages 1-12, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2355-:d:856191
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/13/2355/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/13/2355/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Lingzhong & Yang, Yongqing & Xu, Xianyun, 2018. "Synchronization analysis for fractional order memristive Cohen–Grossberg neural networks with state feedback and impulsive control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 644-660.
    2. Yang, Yongqing & Cao, Jinde, 2007. "Exponential lag synchronization of a class of chaotic delayed neural networks with impulsive effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 492-502.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hualin Song & Cheng Hu & Juan Yu, 2022. "Stability and Synchronization of Fractional-Order Complex-Valued Inertial Neural Networks: A Direct Approach," Mathematics, MDPI, vol. 10(24), pages 1-23, December.
    2. Ben Makhlouf, Abdellatif & Benjemaa, Mondher & Boucenna, Djalal & Hammami, Mohamed Ali, 2023. "Darboux problem for proportional partial fractional differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pratap, A. & Raja, R. & Cao, J. & Lim, C.P. & Bagdasar, O., 2019. "Stability and pinning synchronization analysis of fractional order delayed Cohen–Grossberg neural networks with discontinuous activations," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 241-260.
    2. Ma, Mihua & Zhou, Jin & Cai, Jianping, 2014. "Impulsive practical tracking synchronization of networked uncertain Lagrangian systems without and with time-delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 116-132.
    3. Zhang, Lingzhong & Yang, Yongqing & Wang, Fei, 2017. "Projective synchronization of fractional-order memristive neural networks with switching jumps mismatch," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 402-415.
    4. Zhang, Hai & Chen, Xinbin & Ye, Renyu & Stamova, Ivanka & Cao, Jinde, 2023. "Adaptive quasi-synchronization analysis for Caputo delayed Cohen–Grossberg neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 49-65.
    5. Feng, Xiaomei & Zhang, Fengqin & Wang, Wenjuan, 2011. "Global exponential synchronization of delayed fuzzy cellular neural networks with impulsive effects," Chaos, Solitons & Fractals, Elsevier, vol. 44(1), pages 9-16.
    6. Ma, Mihua & Cai, Jianping & Zhang, Hua, 2019. "Quasi-synchronization of Lagrangian networks with parameter mismatches and communication delays via aperiodically intermittent pinning control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1146-1160.
    7. Weiwei Zhang & Jinde Cao & Dingyuan Chen & Ahmed Alsaedi, 2019. "Out Lag Synchronization of Fractional Order Delayed Complex Networks with Coupling Delay via Pinning Control," Complexity, Hindawi, vol. 2019, pages 1-7, August.
    8. Sheng, Li & Yang, Huizhong & Lou, Xuyang, 2009. "Adaptive exponential synchronization of delayed neural networks with reaction-diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 40(2), pages 930-939.
    9. Zhang, Yanlin & Deng, Shengfu, 2019. "Finite-time projective synchronization of fractional-order complex-valued memristor-based neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 176-190.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2355-:d:856191. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.