Title :
Estimating module relevance with Sugeno integration of modular neural networks using Interval Type-2 Fuzzy logic
Author :
Mendoza, Olivia ; Melin, Patricia ; Licea, Guillermo
Author_Institution :
Sch. of Eng. of UABC, Univ. of Tijuana, Tijuana
Abstract :
In this paper a fuzzy logic approach to determine the relevance of each module in modular neural networks for images recognition is presented. The tests were made with Type-1 and Interval Type-2 Fuzzy Inference Systems, to compare the performance of the proposed approach. In both cases the fusion operator for the modules is the Sugeno Integral, and the estimated parameters are the fuzzy densities.
Keywords :
fuzzy logic; fuzzy neural nets; fuzzy reasoning; image recognition; integration; type theory; Sugeno integration; fuzzy inference system; image recognition; interval type-2 fuzzy logic; modular neural network; module relevance estimation; Fuzzy logic; Hip; Integral equations; Neural networks;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4633970
