HOW NEURAL NETWORKS LEARN FROM EXPERIENCE

被引：221

作者：

HINTON, GE ^{[1
]}

机构：

[1] UNIV TORONTO,COMP SCI & PSYCHOL,TORONTO M5S 1A1,ONTARIO,CANADA

来源：

SCIENTIFIC AMERICAN | 1992年 / 267卷 / 03期

关键词：

D O I：

10.1038/scientificamerican0992-144

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Networks of artificial neurons modeled on conventional computers are helping explain the ability of the brain to process and retain information. These neural-network simulations have already ruled out many theories. They are now beginning to reveal how the brain accomplishes the remarkable feat of learning.

引用

页码：145 / 151

页数：7