Recurrent fuzzy systems
Vittorio Gorrini, Hugues Bersini · 1994
Besides their linguistic interface, we believe fuzzy controllers not only to be universal approximators but also more general and efficient than their similar neural counterparts: radial basis functions. Consequently like recurrent neural networks, this paper aims at extending the fuzzy controllers approximation capacity to dynamic processes of unknown order. We propose a new type of architecture called recurrent fuzzy system together with a learning algorithm for adapting the membership functions.>