Kernel Methods and Its Application in Wavefront Reconstruction
- https://doi.org/10.2991/iccia.2012.28How to use a DOI?
- Kernel PCA, Adaptive optics, Zernike polynomials, Alignment
Kernel methods can effectively deal with the nonlinear problem. The methods not only can be used for data de-noising, also be effective for classification problems. Using kernel PCA method, we provide a more precise Zernike expansion, which can apparently improve the reconstruction accuracy. At the same time, explore learning the kernel function by the alignment. We verify that the alignment value and recognition rate is proportional relationship.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhiying Tan AU - Ying Chen AU - Kun She AU - Yong Feng PY - 2014/05 DA - 2014/05 TI - Kernel Methods and Its Application in Wavefront Reconstruction BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 117 EP - 120 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.28 DO - https://doi.org/10.2991/iccia.2012.28 ID - Tan2014/05 ER -