Self-Adaptive Learning Algorithm for Training Multi-Layered Neural Networks and Its Applications = 다층 신경회로망의 자기 적응 학습과 그 응용

다국어 초록 (Multilingual Abstract)

A problem of making a neural network learning self-adaptive to the training set supplied is addressed in this paper. This arises from the aspect in choice of an adequate stepsize for the update of the current weigh vectors according to the training pairs. Related issues in this attempt are raised and fundamentals in neural network learning are introduced. In comparison to the most popular back-propagation scheme, the usefulness and superiority of the proposed weight update algorithm are illustrated by examing the identification of unknown nonlinear systems only from measurements.