• DocumentCode
    2651587
  • Title

    A T-model neural network with learning ability

  • Author

    Ishizuka, Okihiko ; Tang, Zheng ; Inoue, Tetsuya ; Matsumoto, Hiroki ; Ohba, Shogo

  • Author_Institution
    Dept. of Electron. Eng., Miyazaki Univ., Japan
  • fYear
    1991
  • fDate
    18-21 Nov 1991
  • Firstpage
    2288
  • Abstract
    The authors introduce a novel neural network called the T-model with learning capability. They utilized the least mean square algorithm to train the T-model and exploit the learning capability of the introduced network. The architecture and the algorithm of the T-model network are described. Some typical examples to illustrate the effectiveness of the algorithm are included and compared with the Hopfield model and a multilayer model. The simulations and experiments showed that the algorithm is quite effective in training the T-model network for many problems
  • Keywords
    learning systems; neural nets; parallel architectures; T-model neural network; learning ability; learning systems; least mean square algorithm; Artificial neural networks; Computer networks; Feedforward neural networks; Hopfield neural networks; Least squares approximation; Network synthesis; Neural networks; Neurofeedback; Supervised learning; Telecommunications;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991. 1991 IEEE International Joint Conference on
  • Print_ISBN
    0-7803-0227-3
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.170729
  • Filename
    170729