• DocumentCode
    1064668
  • Title

    Locally recurrent globally feedforward networks: a critical review of architectures

  • Author

    Tsoi, Ah Chung ; Back, Andrew D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Queensland Univ., St. Lucia, Qld., Australia
  • Volume
    5
  • Issue
    2
  • fYear
    1994
  • fDate
    3/1/1994 12:00:00 AM
  • Firstpage
    229
  • Lastpage
    239
  • Abstract
    In this paper, we will consider a number of local-recurrent-global-feedforward (LRGF) networks that have been introduced by a number of research groups in the past few years. We first analyze the various architectures, with a view to highlighting their differences. Then we introduce a general LRGF network structure that includes most of the network architectures that have been proposed to date. Finally we will indicate some open issues concerning these types of networks
  • Keywords
    feedforward neural nets; recurrent neural nets; locally recurrent globally feedforward neural networks; Artificial neural networks; Australia Council; Control systems; Delay; Finite impulse response filter; Input variables; Multilayer perceptrons; Neurofeedback; Neurons; Transfer functions;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.279187
  • Filename
    279187