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  • Learning Capability of T-Model Neural Network

    Okihiko ISHIZUKA  Zheng TANG  Tetsuya INOUE  Hiroki MATSUMOTO  

     
    PAPER-Neural Networks

      Vol:
    E75-A No:7
      Page(s):
    931-936

    We introduce a novel neural network called the T-Model and investigates the learning ability of the T-Model neural network. A learning algorithm based on the least mean square (LMS) algorithm is used to train the T-Model and produces a very good result for the T-Model network. We present simulation results on several practical problems to illustrate the efficiency of the learning techniques. As a result, the T-Model network learns successfully, but the Hopfield model fails to and the T-Model learns much more effectively and more quickly than a multi-layer network.