IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v152y2021ics0960077921007785.html
   My bibliography  Save this article

Deterministic coherence and anti-coherence resonances in networks of chaotic oscillators with frequency mismatch

Author

Listed:
  • Jaimes-Reátegui, R.
  • García-López, J.H.
  • Gallegos, A.
  • Huerta Cuellar, G.
  • Chholak, P.
  • Pisarchik, A.N.

Abstract

We provide compelling numerical evidence of deterministic coherence and anti-coherence resonance in small networks of unidirectional coupled chaotic Rössler oscillators in star and star-ring configurations in the presence of a small mismatch between natural frequencies of the oscillators. The resonance phenomena are found in both the normalized standard deviations of the peak amplitude and inter-peak time interval with respect to the coupling strength and frequency mismatch. The deterministic coherence/anti-coherence resonance resembles self-stabilization/destabilization of the network when the coupling makes collective dynamics more regular/irregular.

Suggested Citation

  • Jaimes-Reátegui, R. & García-López, J.H. & Gallegos, A. & Huerta Cuellar, G. & Chholak, P. & Pisarchik, A.N., 2021. "Deterministic coherence and anti-coherence resonances in networks of chaotic oscillators with frequency mismatch," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
  • Handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921007785
    DOI: 10.1016/j.chaos.2021.111424
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921007785
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2021.111424?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andreev, Andrey V. & Makarov, Vladimir V. & Runnova, Anastasija E. & Pisarchik, Alexander N. & Hramov, Alexander E., 2018. "Coherence resonance in stimulated neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 80-85.
    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. Lev Ryashko & Irina Bashkirtseva, 2022. "Stochastic Bifurcations and Excitement in the ZS-Model of a Thermochemical Reaction," Mathematics, MDPI, vol. 10(6), pages 1-11, March.
    2. Bashkirtseva, Irina & Ryashko, Lev, 2022. "Stochastic generation and shifts of phantom attractors in the 2D Rulkov model," Chaos, Solitons & Fractals, Elsevier, vol. 159(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. Bashkirtseva, Irina & Ryashko, Lev, 2022. "Stochastic generation and shifts of phantom attractors in the 2D Rulkov model," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    2. D’Onofrio, Giuseppe & Lansky, Petr & Tamborrino, Massimiliano, 2019. "Inhibition enhances the coherence in the Jacobi neuronal model," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 108-113.
    3. Slepukhina, Evdokiia & Bashkirtseva, Irina & Ryashko, Lev & Kügler, Philipp, 2022. "Stochastic mixed-mode oscillations in the canards region of a cardiac action potential model," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    4. Bashkirtseva, Irina A. & Ryashko, Lev B. & Pisarchik, Alexander N., 2020. "Ring of map-based neural oscillators: From order to chaos and back," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    5. Masoliver, Maria & Masoller, Cristina & Zakharova, Anna, 2021. "Control of coherence resonance in multiplex neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    6. Guo, Yitong & Xie, Ying & Ma, Jun, 2023. "Nonlinear responses in a neural network under spatial electromagnetic radiation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    7. Slepukhina, Evdokia & Bashkirtseva, Irina & Ryashko, Lev, 2020. "Stochastic spiking-bursting transitions in a neural birhythmic 3D model with the Lukyanov-Shilnikov bifurcation," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    8. Belyaev, Alexander & Bashkirtseva, Irina & Ryashko, Lev, 2021. "Stochastic variability of regular and chaotic dynamics in 2D metapopulation model," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).

    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:eee:chsofr:v:152:y:2021:i:c:s0960077921007785. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.