A hybrid fuzzy neural system as nonlinear system identifier
E.I. Stefanis, John B. Theocharis, George Vachtsevanos · 2002
A hybrid fuzzy neural architecture is proposed. The fuzzy neural system is a feedforward network that combines the basic notions of neural networks and fuzzy logic into a common structure. A back-propagation algorithm is used to train the FNS to perform the desired nonlinear mappings. Four simulation examples are presented where the fuzzy neural system is employed as a nonlinear identifier. Finally, comparisons between fuzzy neural systems, backpropagation neural networks and other fuzzy systems are given and discussed.