DocumentCode
2910078
Title
Layered MVL neural networks capable of recognizing translated characters
Author
Watanabe, Tatsuki ; Matsumoto, Masayuki
Author_Institution
Dept. of Electr. & Electron. Eng., Toyo Univ., Saitama, Japan
fYear
1992
fDate
27-29 May 1992
Firstpage
88
Lastpage
95
Abstract
The multivalued logic (MVL) neurons constituting the layered MVL neural network use MVL operations to produce analog responses to be fed to the respective quantizers. A four-layered MVL neural network model capable of recognizing translated characters is presented. Translation of input characters is easily carried out because MVL neural networks have the unique ability that the input patterns for which such a network has been trained can be reproduced directly from the states of synapse weights. Simulation results showing successful recognition of translated characters are presented
Keywords
character recognition; many-valued logics; neural nets; analog responses; layered multiple valued logic neural networks; quantizers; simulation results; synapse weights; translated characters recognition; Algebra; Boolean functions; Character recognition; Computational modeling; Computer simulation; Logic functions; Multi-layer neural network; Neural networks; Neurons; Pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Multiple-Valued Logic, 1992. Proceedings., Twenty-Second International Symposium on
Conference_Location
Sendai
Print_ISBN
0-8186-2680-1
Type
conf
DOI
10.1109/ISMVL.1992.186782
Filename
186782
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