Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2000.11d
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- Pages.797-799
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- 2000
Digits Recognition Using a Non-Iterative Neural Network
비반복적 훈련 신경망을 이용한 숫자인식
- Lee, Jae-Seung (Dept. of Electrical Eng. Dongguk Univ.) ;
- Ahn, Do-Rang (Dept. of Electrical Eng. Dongguk Univ.) ;
- Lee, Dong-Wook (Dept. of Electrical Eng. Dongguk Univ.)
- Published : 2000.11.25
Abstract
Most neural network learning schemes are derived from learning systems which are generally iterative in nature. But, when the given input-output training vector pairs satisfy a PLI condition, the training and the application of a hard-limited neural network can be achieved non-iteratively with very short training time and very robust recognition when it is applied to recognize any untrained patterns. In this paper, a method of expanding the dimension of training pattern data is suggested. The proposed method demonstrates better performance and robustness.
Keywords