• DocumentCode
    2565416
  • Title

    A reconfigurable CMOS neural network

  • Author

    Graf, H.P. ; Henderson, Dale

  • Author_Institution
    AT&T Bell Lab., Holmdel, NJ, USA
  • fYear
    1990
  • fDate
    14-16 Feb. 1990
  • Firstpage
    144
  • Lastpage
    145
  • Abstract
    An analog CMOS neural net with a programmable architecture containing 32 K connections is discussed. The objective of packing as large a network as possible on a chip leads to the choice of an analog approach. Analog signals are used only inside the network. All the input and output data are digital. The reconfigurable network consists of building blocks that can be joined to form various network architectures. The circuit can be programmed to implement single-layer networks or multilayer networks with binary or analog connections.<>
  • Keywords
    CMOS integrated circuits; analogue computer circuits; neural nets; analog CMOS neural net; multilayer networks; programmable architecture; reconfigurable network; single-layer networks; Analog computers; Circuits; Concatenated codes; Current supplies; Mirrors; Neural networks; Neurons; Registers; Switches; Wire;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Solid-State Circuits Conference, 1990. Digest of Technical Papers. 37th ISSCC., 1990 IEEE International
  • Conference_Location
    San Francisco, CA, USA
  • Type

    conf

  • DOI
    10.1109/ISSCC.1990.110168
  • Filename
    110168