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Modeling of Memristive Devices for Neuromorphic Application

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Real-Time Modelling and Processing for Communication Systems

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 29))

Abstract

This chapter presents the physical mechanism analysis and the compact behavioral modeling of the titanium oxide, ferroelectric tunnel junctions, and phase change materials memristive devices. The memristive devices mathematical theoretical model’s derivation and physics-based model structure representations along with their resistive switching mechanisms are analyzed, implemented and validated. The accuracy of the implemented Verilog-A models of the considered memristive deivces are assessed in a synaptic transmission through spike-timing-dependent plasticity. Moreover, the key properties and performances of these three memristors technologies are discussed in order to classify them and study their adequacy for their adoption to artificially imitate synaptic functionality in neuromorphic applications.

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Author information

Authors and Affiliations

  1. Electronics and Microelectronics Laboratory, National Engineering School of Monastir (ENIM), University of Monastir, 5019, Monastir, Tunisia

    Fakhreddinne Zayer & Hamdi Belagcem

  2. Institut National des Sceinces Appliquées et de Technologies de Sousse, Sousse, Tunisia

    Wael Dghais

Authors
  1. Fakhreddinne Zayer
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  2. Wael Dghais
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  3. Hamdi Belagcem
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Correspondence to Fakhreddinne Zayer .

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Editors and Affiliations

  1. School of Cyberspace, Hangzhou Dianzi University, Hangzhou, Zhejiang, China

    Muhammad Alam

  2. Department of Electronics, Institut Supérieur des Sciences Appliquées et de Technologie de Sousse, Université de Sousse, Sousse , Tunisia

    Wael Dghais

  3. School of Cyberspace, Hangzhou Dianzi University, Hangzhou, Zhejiang, China

    Yuanfang Chen

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Zayer, F., Dghais, W., Belagcem, H. (2018). Modeling of Memristive Devices for Neuromorphic Application. In: Alam, M., Dghais, W., Chen, Y. (eds) Real-Time Modelling and Processing for Communication Systems. Lecture Notes in Networks and Systems, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-319-72215-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-72215-3_8

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  • Online ISBN: 978-3-319-72215-3

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