• DocumentCode
    2740941
  • Title

    CMOL-Based Cellular Neural Networks and Parallel Processor for Future Image Processing

  • Author

    Zhang, Wancheng ; Wu, Nan-Jian

  • Author_Institution
    State Key Lab. for Superlattices & Microstructures, Chinese Acad. of Sci., Beijing
  • fYear
    2008
  • fDate
    18-21 Aug. 2008
  • Firstpage
    737
  • Lastpage
    740
  • Abstract
    Hybrid CMOS/molecular (CMOL) circuits are promising for future high-performance VLSIs. Recently, digital and mixed-signal CMOL-based image-processing circuits were proposed. Although these circuits have ultra-high performances, several problems exist. In this paper, CMOL-based analog cellular neural network (CNN) and digital parallel image processor is proposed. The CMOL-based CNN has high speed and good fabrication tolerance. The parallel processor has high peak performance with easy configurability.
  • Keywords
    CMOS integrated circuits; VLSI; cellular neural nets; hybrid integrated circuits; image processing; molecular electronics; nanoelectronics; parallel processing; CMOL-based cellular neural networks; CMOL-based image processing circuits; VLSI; digital parallel image processor; future image processing; hybrid CMOS/molecular circuits; parallel processor; CMOS memory circuits; CMOS process; CMOS technology; Cellular neural networks; Image processing; Laboratories; Pins; Semiconductor superlattices; Switches; Switching circuits;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nanotechnology, 2008. NANO '08. 8th IEEE Conference on
  • Conference_Location
    Arlington, TX
  • Print_ISBN
    978-1-4244-2103-9
  • Electronic_ISBN
    978-1-4244-2104-6
  • Type

    conf

  • DOI
    10.1109/NANO.2008.221
  • Filename
    4617203