• DocumentCode
    418093
  • Title

    High density VLSI implementation of a bipolar CNN with reduced programmability

  • Author

    Paasio, Ari ; Flak, Jacek ; Laiho, Mika ; Halonen, Kari

  • Author_Institution
    Microelectron. Lab, Turku Univ., Finland
  • Volume
    3
  • fYear
    2004
  • fDate
    23-26 May 2004
  • Abstract
    In this paper a VLSI implementation of a bipolar CNN with a reduced programmability is described. The programmability of the weights and the bias term is reduced to one bit. Since the programming is digital, the template write time is fast. While losing some generality in the programming, the cell array is still able to perform most of the bipolar CNN templates presented so far. The proposed structure yields a very compact realization in a dense layout. The cell size using a 0.18μm digital CMOS process was 155μm2.
  • Keywords
    CMOS digital integrated circuits; VLSI; cellular neural nets; 0.18 micron; VLSI implementation; bipolar CNN; cell array; cellular neural network; digital CMOS process; digital programming; CMOS process; Cellular neural networks; Circuits; Energy consumption; Hardware; Laboratories; Nonlinear equations; Switches; Variable structure systems; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2004. ISCAS '04. Proceedings of the 2004 International Symposium on
  • Print_ISBN
    0-7803-8251-X
  • Type

    conf

  • DOI
    10.1109/ISCAS.2004.1328673
  • Filename
    1328673