| 摘要: |
| The problem of variable selection in system identification of a high dimensional nonlinear non-parametric system is described. The inherent difficulty, the curse of dimensionality, is introduced. Then its connections to various topics and research areas are briefly discussed, including order determination, pattern recognition, data mining, machine learning, statistical regression and manifold embedding. Finally, some results of variable selection in system identification in the recent literature are presented. |
| 关键词: System identification, variable selection, nonlinear non-parametric system, curse of dimensionality |
| DOI： |
| Received:January 16, 2015Revised:January 28, 2015 |
| 基金项目: |
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| Variable selection in identification of a high dimensional nonlinear non-parametric system |
| E.W. Bai,W. Zhao,W. Zheng |
| (Department of Electrical and Computer Engineering, University of Iowa; School of Electronics, Electrical Engineering and Computer Science, Queen’s University;3.Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences;School of Computing, Engineering and Mathematics, University of Western Sydney) |
| Abstract: |
| The problem of variable selection in system identification of a high dimensional nonlinear non-parametric system is described. The inherent difficulty, the curse of dimensionality, is introduced. Then its connections to various topics and research areas are briefly discussed, including order determination, pattern recognition, data mining, machine learning, statistical regression and manifold embedding. Finally, some results of variable selection in system identification in the recent literature are presented. |
| Key words: System identification, variable selection, nonlinear non-parametric system, curse of dimensionality |
