http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Farrukh Hafiz Nagi (검색결과 1 건)
- 무료
- 기관 내 무료
- 유료
-
Layer-Recurrent Network in Identifying a Nonlinear System
Farah Hani Nordin,Farrukh Hafiz Nagi 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
Layer-Recurrent Network (LRN) is a dynamic neural network and is seen as a promising black box model in identifying a nonlinear system injected with nonlinear input signal. In this paper, LRN will be used to identify a nonlinear, state space 3-axis satellite model. Open loop identification is applied and methodology on nonlinear system identification is presented where the best pair of input and output data is first measured. Using the simulated data, six LRN models are used to identify the satellite dynamics. It is shown that only 200 epochs are needed to train a network to converge to a reasonable mean squared value (mse). LRN output is then compared with the state space model where it shows that LRN model is capable to produce similar results as the state space satellite model without knowing the system’ state and prior knowledge of the system
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
