Factor Neural Network Theory and Its Applications

被引:3
|
作者
Wang, Ye [1 ]
Najjar, Lotfollah [2 ]
机构
[1] Univ Sci & Technol, Sch Automat & Elect Engn, Beijing 100088, Peoples R China
[2] Univ Nebraska, Coll Informat Sci & Technol, Omaha, NE 68182 USA
基金
中国国家自然科学基金;
关键词
Factor space; knowledge representation; factor neural networks (FNN); intelligent computation;
D O I
10.1142/S0219622015500042
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents constructive methods of factor neural network (FNN) and their applications to the study of intelligent computation. Liu Zengliang is the first to apply this theory it to intelligent computation, it allows describing numerically and simulating such intelligence problems as knowledge representation, fuzzy reasoning and intelligent learning. It provides a unified description framework for logical and visual (intelligent) thinking. This theory makes significant progress in exhibiting the intelligence science theorem, the academic view and the research approach of FNN. It motivates the development of intelligence science and other related fields. It also helps the development of the nation's economy.
引用
收藏
页码:239 / 251
页数:13
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