Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Lou Taishan"'
Autor:
Wang Xiaolei, Cao Huiliang, Jiao Yuzhao, Lou Taishan, Ding Guoqiang, Zhao Hongmei, Duan Xiaomin
Publikováno v:
Measurement Science Review, Vol 21, Iss 1, Pp 19-24 (2021)
The noise signal in the gyroscope is divided into four levels: sampling frequency level, device bandwidth frequency level, resonant frequency level, and carrier frequency level. In this paper, the signal in the dual-mass MEMS gyroscope is analyzed. B
Externí odkaz:
https://doaj.org/article/57ae01d899fe403b8abc6df86ce2af70
Autor:
Zhang, Zhenya, Wei, Houyu, Lou, Taishan, Zhang, Jun, Xiao, Yanqiu, Jin, Tingxiang, Tian, Jiean, Li, Xuewei, Liu, Zhengxuan
Publikováno v:
In International Communications in Heat and Mass Transfer December 2024 159 Part B
Publikováno v:
In Digital Signal Processing June 2024 149
Publikováno v:
In Journal of the Franklin Institute March 2024 361(4)
Publikováno v:
In Journal of Molecular Liquids 15 December 2023 392 Part 1
Akademický článek
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Autor:
Lou, Taishan
A robust desensitized cubature Kalman filtering (DCKF) for nonlinear systems with uncertain parameter is proposed. Sensitivity matrices are defined as the integral form, and desensitized cost function is designed by penalizing the posterior covarianc
Externí odkaz:
http://arxiv.org/abs/1512.07675
Autor:
Lou, Taishan, Zhao, Liangyu
Publikováno v:
Acta Astronautica (2016), pp. 60-70
This paper presented a robust integrated navigation algorithm based on a special robust desensitized extended Kalman filtering with analytical gain (ADEKF) during the Mars atmospheric entry. The robust ADEKF is designed by minimizing a new function p
Externí odkaz:
http://arxiv.org/abs/1507.00937
Autor:
Lou, Taishan
The possible methodologies to handle the uncertain parameter are reviewed. The core idea of the desensitized Kalman filter is introduced. A new cost function consisting of a posterior covariance trace and trace of a weighted norm of the state error s
Externí odkaz:
http://arxiv.org/abs/1504.04916
Autor:
Lou, Taishan
Uncertain parameters of state-space models have always been a considerable problem. Consider Kalman filter (CKF) and desensitized Kalman filter (DKF) are two methods to solve this problem. Based on the sensitivity matrix respected to the uncertain pa
Externí odkaz:
http://arxiv.org/abs/1503.08379