• DocumentCode
    1643684
  • Title

    Design of a CMOS analog programmable cellular neural network

  • Author

    Betta, G. F Dalla ; Graffi, S. ; Masetti, G. ; Kovács, Zs M.

  • Author_Institution
    DEIS, Bologna Univ., Italy
  • fYear
    1992
  • Firstpage
    151
  • Lastpage
    156
  • Abstract
    The design of an analog programmable CNN architecture with low-power dissipation in a 1.5-μm CMOS technology is presented. After discussing the design of basic building blocks, the electrical performance of a 10×10 CMOS CNN, consisting of about 8000 MOS transistors, fully simulated at the device level, which can be analog-programmed by varying an external control voltage is discussed. The CNN can perform such functions as noise removal, hole filter, shadow detector, connected component recognition, and edge detector. The power consumption of the circuit is about 60 mW, which is about 1/3 of the power consumption of a previously reported nonprogrammable circuit
  • Keywords
    CMOS integrated circuits; analogue processing circuits; image processing equipment; image recognition; neural chips; 1.5 micron; CMOS IC; MOS transistors; analog programmable cellular neural network; connected component recognition; design; edge detector; hole filter; neural chips; noise removal; shadow detector; CMOS process; CMOS technology; Cellular neural networks; Circuit simulation; Detectors; Energy consumption; Image edge detection; Mirrors; Neural networks; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and their Applications, 1992. CNNA-92 Proceedings., Second International Workshop on
  • Conference_Location
    Munich
  • Print_ISBN
    0-7803-0875-1
  • Type

    conf

  • DOI
    10.1109/CNNA.1992.274339
  • Filename
    274339