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切换自回归过程的非参数学习Nonparametric Learning of Switching Autoregressive Processes |
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| 课程网址: | http://videolectures.net/icml08_fox_nls/ |
| 主讲教师: | Emily Fox |
| 开课单位: | 华盛顿大学 |
| 开课时间: | 2008-08-04 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Vector autoregressive (VAR) processes are useful in describing dynamical phenomena as diverse as speech, financial time-series, and the dancing of honey bees. However, such phenomena often exhibit structural changes over time and the VAR which describe them must also change. For example, the vocal tract of a speaker contracts; a country experiences a recession, a central bank intervention, or some national or global event; a honey bee changes from a waggle to a turn right dance. Some of these changes will appear fre- quently, while others are only rarely observed. In ad- dition, there is always the possibility of a previously unseen dynamic behavior. Thus, we propose a non- parametric approach for learning switching VAR pro- cesses, where we take the state sequence to be Markov.... |
| 关 键 词: | 向量自回归; 工艺参数; 状态序列; 马尔可夫 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-04：lxf |
| 阅读次数: | 41 |