• DocumentCode
    1576629
  • Title

    Implementation of cellular neural networks for heteroassociative and autoassociative memories

  • Author

    Brucoli, Michele ; Carnimeo, Leonarda ; Grassi, Giuseppe

  • Author_Institution
    Dipartmento di Electrotecnica ed Elettronica, Politecnico di Bari, Italy
  • fYear
    1996
  • Firstpage
    63
  • Lastpage
    68
  • Abstract
    A design methodology of cellular neural networks (CNN) for heteroassociative and autoassociative memories is presented. A new synthesis procedure of continuous-time CNN for heteroassociative memories is developed, which assures global stability and robustness to the designed networks. A proper representation of discrete-time CNN characterized by multilevel output junctions is introduced to store memory vectors with b-bit length components. The suggested approach provides considerably simple network architectures suitable for VLSI implementation
  • Keywords
    associative processing; cellular neural nets; content-addressable storage; neural net architecture; autoassociative memory; continuous time cellular neural networks; discrete time cellular neural networks; global stability; heteroassociative memory; memory vectors; multilevel output junctions; network architectures; Associative memory; Asymptotic stability; Cellular neural networks; Design methodology; Electronic mail; Hopfield neural networks; Network synthesis; Neural networks; Robust stability; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on
  • Conference_Location
    Seville
  • Print_ISBN
    0-7803-3261-X
  • Type

    conf

  • DOI
    10.1109/CNNA.1996.566492
  • Filename
    566492