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

被引：154

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

页码：624 / 626

页数：3

共 12 条

[1] CHAND DR, 1978, J ASSOC COMPUT MACH, V17, P78
[2] DUDA RO, 1973, PATTERN ANAL SCENE C
[3] LEONARD JA, 1992, IN PRESS COMPUT CHEM
[4] MacQueen J., 1967, 5 BERKELEY S MATH ST, P281
[5] Medgassy P., 1961, DECOMPOSITION SUPERP
[6] MENDENHALL W, 1983, INTRO PROBABILITY ST
[7] Fast Learning in Networks of Locally-Tuned Processing Units
Moody, John
Darken, Christian J.
[J]. NEURAL COMPUTATION, 1989, 1 (02) : 281 - 294
[8] Universal Approximation Using Radial-Basis-Function Networks
Park, J.
Sandberg, I. W.
[J]. NEURAL COMPUTATION, 1991, 3 (02) : 246 - 257
[9] ESTIMATION OF A PROBABILITY DENSITY-FUNCTION AND MODE
PARZEN, E
[J]. ANNALS OF MATHEMATICAL STATISTICS, 1962, 33 (03): : 1065 - &
[10] PROBABILISTIC NEURAL NETWORKS
SPECHT, DF
[J]. NEURAL NETWORKS, 1990, 3 (01) : 109 - 118

← 1 2 →