• DocumentCode
    1295383
  • Title

    Mixed analogue-digital artificial-neural-network architecture with on-chip learning

  • Author

    Schmid, A. ; Leblebici, Y. ; Mlynek, D.

  • Author_Institution
    Dept. of Electr. Eng., Swiss Fed. Inst. of Technol., Lausanne, Switzerland
  • Volume
    146
  • Issue
    6
  • fYear
    1999
  • fDate
    12/1/1999 12:00:00 AM
  • Firstpage
    345
  • Lastpage
    349
  • Abstract
    The authors present a novel artificial-neural-network architecture with on-chip learning capability. The issue of straightforward design-flow integration of an autonomous unit is addressed with a mixed analogue-digital approach, by implementing a charge-based artificial neural network which interacts with digital control and processing units. The circuit architecture and design-flow approach for the case of a Hamming network performing pixel-pattern recognition are described
  • Keywords
    hardware description languages; integrated circuit design; learning (artificial intelligence); mixed analogue-digital integrated circuits; neural chips; reconfigurable architectures; Hamming network; autonomous unit; circuit architecture; design-flow integration; digital control; digital processing units; mixed analogue-digital artificial-neural-network architecture; on-chip learning; reconfigurable architecture;
  • fLanguage
    English
  • Journal_Title
    Circuits, Devices and Systems, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2409
  • Type

    jour

  • DOI
    10.1049/ip-cds:19990685
  • Filename
    819801