DocumentCode
2618096
Title
Fuzzy feature extraction using a class of neural network
Author
Wong, Francis ; Wang, P.Z.
Author_Institution
Inst. of Syst. Sci., Nat. Univ. of Singapore, Singapore
fYear
1991
fDate
18-21 Nov 1991
Firstpage
1618
Abstract
The authors present a novel approach to feature extraction using a class of neural networks for the purpose of authorship recognition. The framework of the research is based on the factor space theory proposed by P.Z. Wang (1990). The main advantage of this approach compared to others is that the dimension of the state space required to distinguish the output patterns for a particular recognition problem can be reduced to the minimum; as a result, both the computation time and the memory storage can be reduced substantially
Keywords
computerised pattern recognition; fuzzy set theory; learning systems; neural nets; state-space methods; authorship recognition; character recognition; computation time; factor space theory; fuzzy feature extraction; fuzzy set theory; learning systems; memory storage; neural network; pattern recognition; state space; Associative memory; Decision making; Expert systems; Feature extraction; Fuzzy neural networks; Instruments; Knowledge based systems; Neural networks; Pattern recognition; State-space methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN
0-7803-0227-3
Type
conf
DOI
10.1109/IJCNN.1991.170360
Filename
170360
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