Parameter Adaptationin in Neural Network Using Fuzzy

퍼지를 이용한 신경망에서의 파라미터의 수정

Back-propagation is one of the efficient algorithms used to nonlinear optimizations or controls. In spite of its structual simplicity and learning ability, learning time is very long or bad case converge local minimum on complicate input patterns. In order to improve these matters varing learning rate and momentums were proposed. In this paper, to improve its performance fuzzy is adjusted in parameters, learning rate and momentums. Parameters are adjusted by errors and change of errors adaptively. In order to evaluate proposed method simulated with MATLAB on inverted pendulum.