DocumentCode :
2676949
Title :
A Novel Fuzzy Neural Network for Pattern Recognition
Author :
Zhao, Yibiao ; Wang, Song ; Zhang, Shun ; Pu, Jian ; Fang, Rui
Author_Institution :
Sch. of Traffic & Transp., Beijing Jiaotong Univ.
Volume :
1
fYear :
2006
fDate :
17-19 July 2006
Firstpage :
286
Lastpage :
291
Abstract :
Neural network system is a self-learning adaptive system, and it is easy to associate, synthesize and generalize with its properties of fault-tolerance and robustness. Therefore, it is available to process the pattern information, which is hard to describe with language. In consideration of the shortage of fuzzy theory and the advantage of vague set, that is fuzzy membership function has only one single value; it cannot get more reasonable classified and cognizable results. While vague sets´ distinguishing feature is having two values which present both of the opposite factors to deal with nonlinearities and uncertain system. In this paper, we define new fuzzy neurons and propose the structure of vague neural network (VNN), and then we expounded the recognition method based on it
Keywords :
fuzzy neural nets; pattern recognition; fuzzy membership function; fuzzy neural network; fuzzy neurons; pattern recognition; self-learning adaptive system; vague neural network; Adaptive systems; Fault tolerant systems; Fuzzy neural networks; Fuzzy set theory; Network synthesis; Neural networks; Neurons; Pattern recognition; Robustness; Uncertain systems; Fuzzy neural network; Information proceeding method; Pattern recognition; Vague set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0475-4
Type :
conf
DOI :
10.1109/COGINF.2006.365508
Filename :
4216425
Link To Document :
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