Application of interval type-2 fuzzy logic for estimating module relevance in Sugeno integration of modular neural networks
Olivia D. Mendoza, Patricia Melín, Oscar Castillo · 2009
In this work we describe a fuzzy inference system to determine the relevance of each module in modular neural networks for images recognition. The tests were made with Type 1 and Interval type-2 fuzzy inference system, to compare the performance. In both cases the fusion operator for the modules is the Sugeno integral, and the parameters to estimate are the fuzzy densities.