Learning method of the ADALINE using the fuzzy logic system

Abstract

We propose a learning method for the ADA-LINE. The proposed method exploits fuzzy logic system for automatic tuning of the weights of the ADALINE. The inputs of the fuzzy logic system are error and change of error, and the output is the weight variation. We used same membership functions and different scaling factor for each weights. In order to verify the effectiveness of the proposed method, we performed the simulation and experimentation for the cases of the noise cancellation and the inverted pendulum control. The results show that the proposed method does not need the learning rate and the derivative, and improves the performance compared to the Widrow-Hoff delta rule for ADALINE.

Noise removal in electroencephalogram signals using an artificial neural network based on the simultaneous perturbation method

“…The proposed system in the present study is consisted of a structure similar to the Adaline [44][45][46]55] (Fig. 1).…”