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Proceedings Paper

Identification of nonlinear optical systems using adaptive kernel methods
Author(s): Xiaodong Wang; Changjiang Zhang; Haoran Zhang; Genliang Feng; Xiuling Xu
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Paper Abstract

An identification approach of nonlinear optical dynamic systems, based on adaptive kernel methods which are modified version of least squares support vector machine (LS-SVM), is presented in order to obtain the reference dynamic model for solving real time applications such as adaptive signal processing of the optical systems. The feasibility of this approach is demonstrated with the computer simulation through identifying a Bragg acoustic-optical bistable system. Unlike artificial neural networks, the adaptive kernel methods possess prominent advantages: over fitting is unlikely to occur by employing structural risk minimization criterion, the global optimal solution can be uniquely obtained owing to that its training is performed through the solution of a set of linear equations. Also, the adaptive kernel methods are still effective for the nonlinear optical systems with a variation of the system parameter. This method is robust with respect to noise, and it constitutes another powerful tool for the identification of nonlinear optical systems.

Paper Details

Date Published: 29 December 2005
PDF: 7 pages
Proc. SPIE 6028, ICO20: Lasers and Laser Technologies, 602827 (29 December 2005); doi: 10.1117/12.667340
Show Author Affiliations
Xiaodong Wang, Zhejiang Normal Univ. (China)
Changjiang Zhang, Zhejiang Normal Univ. (China)
Haoran Zhang, Zhejiang Normal Univ. (China)
Genliang Feng, Zhejiang Normal Univ. (China)
Xiuling Xu, Zhejiang Normal Univ. (China)

Published in SPIE Proceedings Vol. 6028:
ICO20: Lasers and Laser Technologies
Y. C. Chen; Dianyuan Fan; Chunqing Gao; Shouhuan Zhou, Editor(s)

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