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
Link To Document :
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