Factor Neural Network Theory and Its Applications

Abstract

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.