• DocumentCode
    928846
  • Title

    A high-precision VLSI winner-take-all circuit for self-organizing neural networks

  • Author

    Choi, Joongho ; Sheu, Bing J.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
  • Volume
    28
  • Issue
    5
  • fYear
    1993
  • fDate
    5/1/1993 12:00:00 AM
  • Firstpage
    576
  • Lastpage
    584
  • Abstract
    The design and implementation of a high-precision VLSI winner-take-all (WTA) circuit that can be arranged to process 1024 inputs are presented. The cascade configuration can be used to significantly increase the competition resolution and maintain high-speed operation for a large-scale network. The total bias current increases in proportion to the number of circuit cells so that a nearly constant response time is achieved. A unique dynamic current steering method is used to ensure that only a single winner exits in the final output. Experimental results for a prototype chip fabricated in a 2-μm CMOS technology show that a cell can be a winner if its input is larger than those of the other cells by 15 mV. The measured response time is around 50 ns at a 1-pF load capacitance. This analog winner-take-all circuit is a key module in the competitive layer of self-organizing neural networks
  • Keywords
    CMOS integrated circuits; VLSI; neural chips; self-organising feature maps; 1 pF; 2 micron; 50 ns; CMOS technology; VLSI winner-take-all circuit; WTA circuits; cascade configuration; constant response time; dynamic current steering; high-speed operation; large-scale network; prototype chip; self-organizing neural networks; total bias current; CMOS technology; Capacitance measurement; Circuits; Delay; Large-scale systems; Neural networks; Prototypes; Semiconductor device measurement; Time measurement; Very large scale integration;
  • fLanguage
    English
  • Journal_Title
    Solid-State Circuits, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    0018-9200
  • Type

    jour

  • DOI
    10.1109/4.229397
  • Filename
    229397