Identification of nonlinear optical systems using adaptive kernel methods

Xiaodong Wang; Changjiang Zhang; Haoran Zhang; Genliang Feng; Xiuling Xu

doi:10.1117/12.667340

29 December 2005 Identification of nonlinear optical systems using adaptive kernel methods

Xiaodong Wang, Changjiang Zhang, Haoran Zhang, Genliang Feng, Xiuling Xu

Proceedings Volume 6028, ICO20: Lasers and Laser Technologies; 602827 (2005) https://doi.org/10.1117/12.667340
Event: ICO20:Optical Devices and Instruments, 2005, Changchun, China

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.

Citation Download Citation

Xiaodong Wang, Changjiang Zhang, Haoran Zhang, Genliang Feng, and Xiuling Xu "Identification of nonlinear optical systems using adaptive kernel methods", Proc. SPIE 6028, ICO20: Lasers and Laser Technologies, 602827 (29 December 2005); https://doi.org/10.1117/12.667340

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available