대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 1997년도 하계학술대회 논문집 B
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- Pages.386-389
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- 1997
플랜트구조와 신경망에뮬레이터의 구조 및 학습시간과의 관계
A study on interrelation between the structure of a Plant and the str neural network emulator and the learning rate
- Pae, Chang-Han (Ajou University) ;
- Lee, Kwang-Won (Ajou University)
- 발행 : 1997.07.21
초록
Error-backpropagation has been used in the bulk of Practical applications for neural networks. While an emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. There is, however, no concrete theoretical results about the structure of a plant and the structure of a multilayered neural network and the learning rate. The paper investigates the relation between structure of a plant and a multilayered network and learning rate. Simulation study shows that the plant signal with a short period and a fast sam time is preferable for learning of the network emulator.
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