Pattern Classification Based On Radial Basis Function Neural Network

被引：2
|
作者：
Zhang, Zhongwei [1 ]
机构：
[1] Chinese Acad Sci, Natl Space Sci Ctr, Beijing 100190, Peoples R China
来源：
2020 5TH INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2020) | 2020年
关键词：
Pattern recognition; Radial Basis Function Neural Network; Classification;
D O I：
10.1109/ICSGEA51094.2020.00052
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Radial Basis Function (RBF) neural network is a kind of forward network with good performance. It has the properties of global approximation, and has the linear relationship of output weights on the network structure. At the same time, the training speed of the network is fast. The RBF neural network also has close relation with Convolutional neural network (CNN), can avoid the local optimal problem, so the network gets more and more attention in the pattern recognition application. In this paper, the significance of RBF neural network is described, and the difference between RBF and other neural networks is introduced, and the development trend of RBF neural network is illustrated.
引用
收藏
页码：213 / 216
页数：4
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