• DocumentCode
    1797268
  • Title

    The state of the art of memristive neural systems: Models and applications

  • Author

    Ailong Wu ; Zhigang Zeng ; Chaojin Fu

  • Author_Institution
    Coll. of Math. & Stat., Hubei Normal Univ., Huangshi, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    2831
  • Lastpage
    2836
  • Abstract
    Memristive neural systems are a groundbreaking concept that is helping to understand the behavior of many physical, technical and bionic systems. This paper reviews the research status of memristive neural systems in the past few years. Considering there are too many publications about the memristive neural systems, we summarize the relevant models and applications rather than contemplating to go into details of particular results. First, some representative models of memristive neural systems are simply introduced. Then, we briefly describe some novel applications in the related fields (dynamic information storage or retrieval, logical operations and ultra-high-performance computing). Subsequently, some existing problems are summarized, and finally, the trend of memristive neural systems is pointed out.
  • Keywords
    memristors; neural chips; dynamic information retrieval; dynamic information storage; logical operations; memristive neural systems; ultra-high-performance computing; Automata; Biological neural networks; Chaos; Computer architecture; Educational institutions; Memristors; Neuromorphics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2014 International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6627-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2014.6889375
  • Filename
    6889375