Factor Neural Network Theory and Its Applications

Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 147)

Abstract

The Factor Neural Network Theory (FNN) and its applications are introduced in this paper. The Factor Neural Network theory to model intelligent computation was founded by Liu Zengliang, etc [2,7]. Based on this theory, intelligence problems such as the knowledge representation, fuzzy reasoning and associated learning could be quantitatively described and simulated. And the unified description of the logical and visual thinking could be implemented. This theory made significant progress in exhibit 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. The project obtained prominent recognition and acknowledgement from L.A. Zadeh, Koczy [2], Li Guojie[3]and other domain experts.

Keywords

Factor space approach for knowledge representation Factor Neural Networks (FNN) intellectualized computing 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Foreign Affairs Office of National Defense UniversityBeijingChina
  2. 2.Beijing Insititute of TechnologyBeijingChina

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