• DocumentCode
    295863
  • Title

    Placement with self-organising neural networks

  • Author

    Zamani, M. Saheb ; Hellestrand, G.R.

  • Author_Institution
    Sch. of Comput. Sci. & Eng., New South Wales Univ., Sydney, NSW, Australia
  • Volume
    5
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    2185
  • Abstract
    This paper introduces a neural network approach to node placement in an arbitrarily shaped rectilinear boundary based on self-organising principle. An abstract specification of the design is converted to a set of appropriate input vectors fed to the network at random. At the end of the process, the map shows the rectilinear shape 2-dimensional plane of the design in which the modules with higher connectivity to each other and also to some external ports are placed close to each other, hence minimising total connection length in the design
  • Keywords
    circuit layout CAD; circuit optimisation; iterative methods; network topology; self-organising feature maps; 2D plane; Kohonen self organising map; abstract specification; input vectors; module connectivity; node placement; optimisation; self-organising neural networks; shaped rectilinear boundary; Circuits; Macrocell networks; Neural networks; Neurons; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.487699
  • Filename
    487699