• DocumentCode
    1674153
  • Title

    VLSI implementation of a learning actractor neuronal network (LANN)

  • Author

    Bertazzoni, S. ; Cardarilli, G.C. ; Lojacono, R. ; Salmeri, M. ; Salsano, A. ; Simonelli, O.

  • Author_Institution
    Dept. of Electron. Eng., Rome Univ., Italy
  • fYear
    1995
  • Firstpage
    331
  • Lastpage
    333
  • Abstract
    In this paper we describe the most important steps of the VLSI analog implementation of a learning actractor neural network. An overview of the theoretical model is presented while the most important circuits are described in greater details
  • Keywords
    Hopfield neural nets; VLSI; analogue processing circuits; learning (artificial intelligence); neural chips; Hopfield networks; LANN; VLSI implementation; analog implementation; learning actractor neuronal network; theoretical model; Biological neural networks; Circuits; Equations; Hardware; Multilayer perceptrons; Neural networks; Neurons; Software algorithms; Statistics; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Solid-State and Integrated Circuit Technology, 1995 4th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-3062-5
  • Type

    conf

  • DOI
    10.1109/ICSICT.1995.500156
  • Filename
    500156
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1674153