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LEARNING CAPABILITY OF T-MODEL NEURAL NETWORK
被引:0
|作者:
ISHIZUKA, O
TANG, Z
INOUE, T
MATSUMOTO, H
机构:
来源:
关键词:
NEURAL NETWORK;
FULLY INTERCONNECTION;
HALF INTERCONNECTION;
FEEDFORWARD NETWORK;
D O I:
暂无
中图分类号:
TP3 [计算技术、计算机技术];
学科分类号:
0812 ;
摘要:
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.
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页码:931 / 936
页数:6
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