DocumentCode :
2557888
Title :
Neural nets as models for study of multivalued logic
Author :
Pao, Yoh-Han
Author_Institution :
Center for Autom. & Intelligent Syst. Res., Case Western Reserve Univ., Cleveland, OH, USA
fYear :
1988
fDate :
0-0 1988
Firstpage :
142
Abstract :
Summary form only given. It is suggested that since one can now implement neural nets which can actually perform certain basic information processing functions, it is of interest to see if one can fashion nets or systems of nets which can reproduce (i.e. mimic) certain trains of actions regularly performed by humans. The particular issue addressed is that of implementing a multivalued logic system in a neural net, concentrating on one such logic system, namely fuzzy set logic. The focus is on how a network might be used to describe a membership function and how a (multivalued) fuzzy logic system might also be accommodated with such a net.<>
Keywords :
fuzzy set theory; many-valued logics; neural nets; fuzzy set logic; information processing functions; membership function; models; multivalued logic; neural nets; Automation; Biological system modeling; Biology computing; Concurrent computing; Distributed computing; Fuzzy logic; Intelligent systems; Multivalued logic; Neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multiple-Valued Logic, 1988., Proceedings of the Eighteenth International Symposium on
Conference_Location :
Palma de Mallorca, Spain
Print_ISBN :
0-8186-0859-5
Type :
conf
DOI :
10.1109/ISMVL.1988.5166
Filename :
5166
Link To Document :
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