Neural networks with node gates

被引：0

作者：

Myint, HM ^{[1
]}

Murata, J ^{[1
]}

Nakazono, T ^{[1
]}

Hirasawa, K ^{[1
]}

机构：

[1] Kyushu Univ, Grad Sch Informat Sci & Elect Engn, Higashi Ku, Fukuoka 8128581, Japan

来源：

IEEE RO-MAN 2000: 9TH IEEE INTERNATIONAL WORKSHOP ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION, PROCEEDINGS | 2000年

关键词：

D O I：

10.1109/ROMAN.2000.892504

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Function approximation problems for the ordinary neural networks may be rather difficult if the function becomes complicated, due to the necessity of big network size and the possibilities of many local minima. A promissing way to solve these difficulties a's the localization of the problem. According to this concept, a new architecture of neural network is proposed namely neural network with node gates. In this paper, a function approximation example is provided to demonstrate the better performance of the proposed networks than the ordinary neural network.

引用

页码：253 / 257

页数：5

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