IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v142y2021ics0960077920307797.html
   My bibliography  Save this article

Probabilistic memristive networks: Application of a master equation to networks of binary ReRAM cells

Author

Listed:
  • Dowling, Vincent J.
  • Slipko, Valeriy A.
  • Pershin, Yuriy V.

Abstract

The possibility of using non-deterministic circuit components has been gaining significant attention in recent years. The modeling and simulation of their circuits require novel approaches, as now the state of a circuit at an arbitrary moment in time cannot be predicted deterministically. Generally, these circuits should be described in terms of probabilities, the circuit variables should be calculated on average, and correlation functions should be used to explore interrelations among the variables. In this paper, we use, for the first time, a master equation to analyze the networks composed of probabilistic binary memristors. Analytical solutions of the master equation for the case of identical memristors connected in-series and in-parallel are found. Our analytical results are supplemented by results of numerical simulations that extend our findings beyond the case of identical memristors. The approach proposed in this paper facilitates the development of probabilistic/stochastic electronic circuits and advance their real-world applications.

Suggested Citation

  • Dowling, Vincent J. & Slipko, Valeriy A. & Pershin, Yuriy V., 2021. "Probabilistic memristive networks: Application of a master equation to networks of binary ReRAM cells," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
  • Handle: RePEc:eee:chsofr:v:142:y:2021:i:c:s0960077920307797
    DOI: 10.1016/j.chaos.2020.110385
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077920307797
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2020.110385?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.

    Citations

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


    Cited by:

    1. Guseinov, D.V. & Matyushkin, I.V. & Chernyaev, N.V. & Mikhaylov, A.N. & Pershin, Y.V., 2021. "Capacitive effects can make memristors chaotic," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    2. Agudov, N.V. & Dubkov, A.A. & Safonov, A.V. & Krichigin, A.V. & Kharcheva, A.A. & Guseinov, D.V. & Koryazhkina, M.N. & Novikov, A.S. & Shishmakova, V.A. & Antonov, I.N. & Carollo, A. & Spagnolo, B., 2021. "Stochastic model of memristor based on the length of conductive region," Chaos, Solitons & Fractals, Elsevier, vol. 150(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:142:y:2021:i:c:s0960077920307797. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.