Paper
12 October 2006 Identification of complex Bragg gratings based on optical transfer function estimation using genetic algorithm
A. Rostami, A. Yazdanpanah-Goharrizi, A. Yazdanpanah-Goharrizi, F. Janabi-Sharifi
Author Affiliations +
Proceedings Volume 6374, Optomechatronic Actuators, Manipulation, and Systems Control; 63740X (2006) https://doi.org/10.1117/12.684881
Event: Optics East 2006, 2006, Boston, Massachusetts, United States
Abstract
In this paper an optical transfer function for description of the operation of complex fiber Bragg Gratings similar to electrical ones is presented (H(jω)). For this purpose and reconstruction of the transfer function, the Genetic Algorithm (GA) is used to find optimum number of poles and zeros from the measured reflection coefficient. After building the transfer function according to the developed algorithm in this paper, the reflection coefficient for this approximated system is obtained (simulated) and compared with measured values. The results obtained from the approximated transfer function in these cases are so close to real measured data. So, the presented method introduces an interesting approach for identification of the complex Bragg Gratings in frequency domain. Some of optical characteristics (both frequency domain and time domain parameters) of these systems can be extracted from the approximated transfer function easily.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Rostami, A. Yazdanpanah-Goharrizi, A. Yazdanpanah-Goharrizi, and F. Janabi-Sharifi "Identification of complex Bragg gratings based on optical transfer function estimation using genetic algorithm", Proc. SPIE 6374, Optomechatronic Actuators, Manipulation, and Systems Control, 63740X (12 October 2006); https://doi.org/10.1117/12.684881
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Fiber Bragg gratings

Apodization

Optical transfer functions

Control systems

Genetic algorithms

Algorithm development

Inverse problems

Back to Top