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Learning Method of the ADALINE Using the Fuzzy System  

정경권 (동국대학교 전자공학과)
김주웅 (동국대학교 전자공학과)
정성부 (서일대학 전자과)
엄기환 (동국대학교 전자공학과)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.40, no.1, 2003 , pp. 10-18 More about this Journal
Abstract
In this paper, we proposed a learning algorithm for the ADALINE network. The proposed algorithm exploits fuzzy system for automatic tuning of the weight parameters of the ADALINE network. The inputs of the fuzzy system are error and change of error, and the output is the weight variation. We used different scaling factor for each weights. In order to verify the effectiveness of the proposed algorithm, we peformed the simulation and experimentation for the cases of the noise cancellation and the inverted pendulum control. The results show that the proposed algorithm does not need the learning rate and improves 4he performance compared to the Widrow-Hoff delta rule for ADALINE.
Keywords
Neural network; ADALINE; Fuzzy system; Widrow-Hoff delta rule; Noise cancellation; Inverted pendulum;
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