Universal approximation with uninorm-based fuzzy neural networks
André Lemos, Владик Крейнович, Walmir M. Caminhas, Fernando A. C. Gomide · 2011
Fuzzy neural networks are hybrid models capable to approximate functions with high precision and to generate transparent models, enabling the extraction of valuable information from the resulting topology. In this paper we will show that the recently proposed fuzzy neural network based on weighted uninorms aggregations uniformly approximates any real functions on any compact set. We will describe the network topology and inference mechanism and show that the universal approximation property of this network is valid for a given choice of operators.