• DocumentCode
    2624748
  • Title

    Analogic CNN computing: architectural, implementation, and algorithmic advances-a review

  • Author

    Roska, Tamás

  • Author_Institution
    Analogical & Neural Comput. Lab., Hungarian Acad. of Sci., Budapest, Hungary
  • fYear
    1998
  • fDate
    14-17 Apr 1998
  • Firstpage
    3
  • Lastpage
    10
  • Abstract
    In this paper, first, an overview is given about the whole scenario of analogic cellular neural net (CNN) computing. Next, two areas of CNN computing technology are considered briefly: (i) the architectural advances, especially variable resolution and adaptation in space, time, and value and (ii) the computational infrastructure from high-level language and compiler to physical implementations. Three basic physical implementations are considered: analogic CMOS, emulated digital CMOS and optical. The computational infrastructure is the same for all implementations, except the physical interfaces
  • Keywords
    CMOS analogue integrated circuits; analogue processing circuits; cellular neural nets; neural net architecture; optical neural nets; reviews; analogic CNN computing; analogue CMOS; cellular neural net; compiler; computational infrastructure; emulated digital CMOS; high-level language; neural net architecture; optical implementation; physical implementations; variable resolution; Analog computers; Application software; Cellular neural networks; Cloning; Computer architecture; High level languages; Image processing; Morphology; Physics computing; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications Proceedings, 1998 Fifth IEEE International Workshop on
  • Conference_Location
    London
  • Print_ISBN
    0-7803-4867-2
  • Type

    conf

  • DOI
    10.1109/CNNA.1998.685320
  • Filename
    685320