Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 1995.11a
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- Pages.161-164
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- 1995
The comparison of the performance in the identification between SBP and DBP for a plant with output noise
출력잡음을 가진 플랜트에 대한 SBP 와 DBP의 식별성능 비교
- Jin, Seung-Hee (Dept. of Electrical Engineering, Yonsei University) ;
- Park, Jin-Bae (Dept. of Electrical Engineering, Yonsei University) ;
- Yoon, Tae-Sung (Dept. of Electrical Engineering, Changwon University)
- Published : 1995.11.18
Abstract
This paper introduces an identification model called the Dynamic Neural Network(DNN) with a multilayer neural network in the forward path and a linear dynamical system in the feedback path, and defines Dynamic BackPropagation(DBP) as a learning algorithm for it. This identification model uses the feedback of its own output as a learning signal, which is not affected by a noise added to the output terminal of the plant so, it can be considered as a parallel identification model, and when compared with a series-parallel model which does not use the concept of the feedback, the proposed identification scheme exhibits more robust performance.
Keywords