• DocumentCode
    1769265
  • Title

    Memristor plasticity enables emergence of synchronization in neuromorphic networks

  • Author

    Ascoli, A. ; Tetzlaff, Ronald ; Lanza, Valentina ; Corinto, Fernando ; Gilli, Manfred

  • Author_Institution
    Inst. fur Grundlagen der Elektrotechnik und Elektron., Tech. Univ. Dresden, Dresden, Germany
  • fYear
    2014
  • fDate
    1-5 June 2014
  • Firstpage
    2261
  • Lastpage
    2264
  • Abstract
    Besides being at the core of novel ultra-high density low-power non-volatile memories and innovative pattern recognition systems based upon oscillatory associative and dynamic memories, the nano-scale memristor also has the potential to reproduce the behavior of a biological synapse more efficiently and accurately than any conventional electronic emulator. As in a living being the weight of a synapse is adapted by the ionic flow through it, so the conductance of a memristor is adjusted by the flux across it. This article is organized according to the regulations of the ISCAS2014 special session on the state-of-the-art in memristor-based nonlinear circuits and architectures. In this work we focus on arrays of oscillatory cells locally coupled through memristors. Our investigations shows how the nonlinear dynamics of the memristor plays a key role in the mechanisms underlying the synchronization properties of the networks. This work provides new insights into the nonlinear behavior of the still largely unexplored memristor element, which promises to revolutionize integrated circuit design in the incoming years.
  • Keywords
    content-addressable storage; memristors; nanoelectronics; neural nets; nonlinear network synthesis; plasticity; biological synapse; dynamic memory; electronic emulator; ionic flow; low power memory; memristor based nonlinear circuit; memristor plasticity; nanoscale memristor; neuromorphic network synchronization; nonvolatile memory; oscillatory associative memory; oscillatory cells; pattern recognition system; ultrahigh density; Couplings; Equations; Manganese; Mathematical model; Memristors; Neurons; Synchronization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (ISCAS), 2014 IEEE International Symposium on
  • Conference_Location
    Melbourne VIC
  • Print_ISBN
    978-1-4799-3431-7
  • Type

    conf

  • DOI
    10.1109/ISCAS.2014.6865621
  • Filename
    6865621