• DocumentCode
    1449187
  • Title

    Functional graph model of a neural network

  • Author

    Podolak, Igor T.

  • Author_Institution
    Inst. of Comput. Sci., Jagellonian Univ., Cracow, Poland
  • Volume
    28
  • Issue
    6
  • fYear
    1998
  • fDate
    12/1/1998 12:00:00 AM
  • Firstpage
    876
  • Lastpage
    881
  • Abstract
    A model representing neural networks is proposed. It uses the functional graphs notion defined by R. Jakubowski (1977). This is a system of nodes connected with functional edges between which binary relations can be defined. Multilayer artificial neural networks can easily be defined using functional edges to model neurons, and parametrized binary relations to model synaptic connections. Learning is also defined in terms of functional graphs. The proposed description can produce descriptions of whole classes of networks
  • Keywords
    feedforward neural nets; learning (artificial intelligence); binary relations; functional graph model; functional graphs; learning; multilayer artificial neural networks; neural network; parametrized binary relations; synaptic connections; Artificial neural networks; Computer architecture; Computer science; Feedforward neural networks; Feeds; Hidden Markov models; Multi-layer neural network; Neural networks; Neurons; Numerical models;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4419
  • Type

    jour

  • DOI
    10.1109/3477.735398
  • Filename
    735398