Feed-forward neural networks with sigmoidal and radial basis functions hidden neurons

被引：0

作者：

Valova, I ^{[1
]}

Gueorguieva, N ^{[1
]}

Kempka, M ^{[1
]}

机构：

[1] Massachusetts Univ, N Dartmouth, MA 02747 USA

来源：

2003 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-5, CONFERENCE PROCEEDINGS | 2003年

关键词：

multi-layer perceptron; radial basis functions neural networks; benchmark tests; intertwined spiral problem;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This discussion paper concentrates on a possible combination of different activation functions in the multilayered perceptron (MLP) for classification tasks. The activation functions, which are combined are the sigmoidal and the radial basis function. We propose this approach to modification of MLP as solutions to some of the shortfalls of this network.

引用

页码：1630 / 1635

页数：6

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