PATTERN-RECOGNITION IN HIGH-ENERGY PHYSICS WITH ARTIFICIAL NEURAL NETWORKS - JETNET-2.0

被引：48

作者：

LONNBLAD, L

PETERSON, C

ROGNVALDSSON, T

机构：

[1] Department of Theoretical Physics, University of Lund, S-223 62 Lund

来源：

COMPUTER PHYSICS COMMUNICATIONS | 1992年 / 70卷 / 01期

关键词：

PATTERN RECOGNITION; JET IDENTIFICATION; ARTIFICIAL NEURAL NETWORK;

D O I：

10.1016/0010-4655(92)90099-K

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A F77 package of adaptive artificial neural network algorithms, JETNET 2.0. is presented. Its primary target is the high energy physics community, but it is general enough to be used in any pattern-recognition application area. The basic ingredients are the multilayer perceptron back-propagation algorithm and the topological self-organizing map. The package consists of a set of subroutines, which can either be used with standard options or be easily modified to host alternative architectures and procedures.

引用

页码：167 / 182

页数：16

共 11 条

[1] What Size Net Gives Valid Generalization? [J].