Abstract
We present an alternative neural network architecture which is similar to the operation of a general fuzzy inference system. This hybrid fuzzy neural network (HFNN) is a modified multilayer feedforward neural network (MFNN) with four different layers. By using the gradient method, learning algorithms are derived. An example is presented to compare the approximation performance of the HFNN with the MFNN. The HFNN is then applied to an inverted pendulum control problem by using temporal backpropagation. The performance of the HFNN controller is illustrated by simulations.
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