A Fuzzy Elman Neural Network
نویسندگان
چکیده
A fuzzy Elman neural network (FENN) is proposed to identify and simulate nonlinear dynamic systems. Each of all the fuzzy rules used in FENN has a linear state-space equation as its consequence and the network, by use of firing strengths of input variables, combines these Takagi-Sugeno type rules to represent the modeled nonlinear system. The context nodes in FENN are used to perform temporal recurrence. An online dynamic BP-like learning algorithm is derived. The pendulum system is simulated as a testbed for illustrating the better learning and generalization capability of the proposed FENN network, compared with the common Elman-type networks.
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