역전파 학습의 오차함수 개선에 의한 다층퍼셉트론의 학습성능 향상

Improving the Error Back-Propagation Algorithm of Multi-Layer Perceptrons with a Modified Error Function

In this paper, we propose a modified error function to improve the EBP(Error Back-Propagation) algorithm of Multi-Layer Perceptrons. Using the modified error function, the output node of MLP generates a strong error signal in the case that the output node is far from the desired value, and generates a weak error signal in the opposite case. This accelerates the learning speed of EBP algorothm in the initial stage and prevents overspecialization for training patterns in the final stage. The effectiveness of our modification is verified through the simulation of handwritten digit recognition.