대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 1999년도 하계학술대회 논문집 G
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- Pages.2932-2934
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- 1999
신경망 회로를 이용한 필기체 숫자 인식에 관할 연구
A Study Of Handwritten Digit Recognition By Neural Network Trained With The Back-Propagation Algorithm Using Generalized Delta Rule
- Lee, Kye-Han (Dept. of Control & instrumentation Engineering Kwangwoon Univ) ;
- Chung, Chin-Hyun (Dept. of Control & instrumentation Engineering Kwangwoon Univ)
- 발행 : 1999.07.19
초록
In this paper, a scheme for recognition of handwritten digits using a multilayer neural network trained with the back-propagation algorithm using generalized delta rule is proposed. The neural network is trained with hand written digit data of different writers and different styles. One of the purpose of the work with neural networks is the minimization of the mean square error(MSE) between actual output and desired one. The back-propagation algorithm is an efficient and very classical method. The back-propagation algorithm for training the weights in a multilayer net uses the steepest descent minimization procedure and the sigmoid threshold function. As an error rate is reduced, recognition rate is improved. Therefore we propose a method that is reduced an error rate.
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