A new type of recurrent fuzzy neural network for modeling dynamic systems

In this paper, a new type of neural network called recurrent fuzzy neural network (RFNN) is proposed to model the fuzzy dynamical systems (FDS). FDS is considered as an order system. The network developed in this paper is based on recurrent neural networks (RNN) to capture the dynamical properties of FDS. The training algorithm is derived based on the tool of order derivative. An example is given to demonstrate the validity of the approach. (C) 2001 Elsevier Science B.V. All rights reserved.