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