Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)

Kernel Methods and Its Application in Wavefront Reconstruction

Authors
Zhiying Tan, Ying Chen, Kun She, Yong Feng
Corresponding Author
Zhiying Tan
Available Online May 2014.
DOI
10.2991/iccia.2012.28How to use a DOI?
Keywords
Kernel PCA, Adaptive optics, Zernike polynomials, Alignment
Abstract

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.

Copyright
© 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/).

Download article (PDF)

Volume Title
Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
Series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
978-94-91216-41-1
ISSN
1951-6851
DOI
10.2991/iccia.2012.28How to use a DOI?
Copyright
© 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  - 10.2991/iccia.2012.28
ID  - Tan2014/05
ER  -