Title :
The fuzzy neural networks with ternary encoding
Author :
Semenova, Olga ; Semenov, Alexander ; Koval, K. ; Rudyk, A. ; Chuhov, V.
Author_Institution :
Vinnytsia Nat. Tech. Univ., Vinnytsia, Ukraine
Abstract :
When combining fuzzy logic and neural networks it is possible to get a hybrid system that can process uncertain values and can be trained. Fuzzy logic elements can be regarded as fuzzy-neural networks. In order to present a set of fuzzy values the ternary encoding is used. Three fuzzy neural networks on linear neurons are proposed. The first operates as a fuzzy logical minimum element, the second does as a fuzzy logical maximum element, the third - as a fuzzy logical complement element.
Keywords :
encoding; fuzzy logic; fuzzy neural nets; fuzzy set theory; fuzzy logic elements; fuzzy logical complement element; fuzzy logical maximum element; fuzzy logical minimum element; fuzzy neural networks; fuzzy values; hybrid system; linear neurons; ternary encoding; uncertain value processing; Biological neural networks; Educational institutions; Electronic mail; Encoding; Fuzzy logic; Fuzzy neural networks; Neurons; fuzzy; neural network; ternary;
Conference_Titel :
Control and Communications (SIBCON), 2013 International Siberian Conference on
Conference_Location :
Krasnoyarsk
Print_ISBN :
978-1-4799-1060-1
DOI :
10.1109/SIBCON.2013.6693591
