USING RADIAL BASIS FUNCTIONS TO APPROXIMATE A FUNCTION AND ITS ERROR-BOUNDS

被引：156
作者：
LEONARD, JA [1 ]
KRAMER, MA [1 ]
UNGAR, LH [1 ]
机构：
[1] UNIV PENN,DEPT CHEM ENGN,PHILADELPHIA,PA 19104
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 1992年 / 3卷 / 04期
关键词：
D O I：
10.1109/72.143377
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel network called the validity index network (VI net) is presented. The VI net, derived from radial basis function networks, fits functions and calculates confidence intervals for its predictions, indicating local regions of poor fit and extrapolation.
引用
收藏
页码：624 / 626
页数：3
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