图 书 馆
动力学系统子空间识别的一种统计学习方法A statistical learning approach to subspace identification of dynamical systems |
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| 课程网址: | http://videolectures.net/slsfs05_bie_slasi/ |
| 主讲教师: | Tijl De Bie |
| 开课单位: | 布里斯托大学 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Among the different approaches to identification of linear dynamical systems, subspace identification has become increasingly popular in the last decade. The reasons are the algorithmic simplicity thanks to the absence of non-convex optimization problems, the numerical stabil- ity and the statistical properties. Interestingly, concerning the statistical side, research in subspace identification has been concentrated on proving properties related to asymptotic unbiasedness. In this extended abstract we motivate how the use of an appropriate regularization can be helpful in the small sample case. Furthermore, this regularization allows one to use the kernel trick to identify systems where the input term in the state and output equations is a nonlinear function of the input variables. |
| 关 键 词: | 线性动力系统; 子空间识别; 非凸优化 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-21：cwx |
| 阅读次数: | 57 |