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EUSFLAT
2009
245views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Universal Approximation of a Class of Interval Type-2 Fuzzy Neural Networks Illustrated with the Case of Non-linear Identificati
Neural Networks (NN), Type-1 Fuzzy Logic Systems (T1FLS) and Interval Type-2 Fuzzy Logic Systems (IT2FLS) are universal approximators, they can approximate any non-linear function....
Juan R. Castro, Oscar Castillo, Patricia Melin, An...
DLOG
2006
13 years 9 months ago
Handling Imprecise Knowledge with Fuzzy Description Logic
Fuzzy Description Logics have been proposed in the literature as a way to represent and reason with vague and imprecise knowledge. Their decidability, the empirically tractable an...
Giorgos Stoilos, Giorgos B. Stamou, Jeff Z. Pan
IJSYSC
2006
127views more  IJSYSC 2006»
13 years 7 months ago
Backlash compensation of nonlinear systems using fuzzy logic
: A backlash compensator is designed for nonlinear systems using the fuzzy logic. The classification property of fuzzy logic systems makes them a natural candidate for the rejectio...
Jun Oh Jang, Gi Joon Jeon
KI
1992
Springer
13 years 11 months ago
How to Construct a Logic for Your Application
Abstract. The purpose of this note is to present and evaluate the options available to a researcher wishing to use logic for representation, reasoning and computation in his applic...
Dov M. Gabbay
EUSFLAT
2009
156views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
On Classical, Fuzzy Classical, Quantum and Fuzzy Quantum Systems
In this paper we consider physical systems and the concept of their states in the context of the theory of fuzzy sets and systems. In section 1 we give a brief sketch on the fundam...
Rudolf Seising