Hybridization of neural networks and genetic algorithms for identification of complex Bragg gratings

Ali Rostami; Arash Yazdanpanah-Goharrizi; Amin Yazdanpanah-Goharrizi; F. Janabi-Sharifi

doi:10.1117/12.684880

12 October 2006 Hybrid neural networks and genetic algorithms for identification of complex Bragg gratings

Ali Rostami, Arash Yazdanpanah-Goharrizi, Amin Yazdanpanah-Goharrizi, F. Janabi-Sharifi

Proceedings Volume 6374, Optomechatronic Actuators, Manipulation, and Systems Control; 63740W (2006) https://doi.org/10.1117/12.684880
Event: Optics East 2006, 2006, Boston, Massachusetts, United States

Abstract

In this paper a novel method for investigation of inverse scattering in optical complex mediums is proposed. The proposed method is based on Radial Basis Function Neural Networks (RBFNN) and Genetic Algorithms (GAs). Medium discrimination is performed by RBFNN and corresponding medium parameters identification is done using GAs. In the proposed method for simplicity the apodized, chirped and simultaneously apodized and chirped types of mediums are considered as RBFNN library. The proposed method tries to open a new insight to inverse scattering in optical devices and systems identification. The simulated results closely follow full numerical simulations to illustrate the ability of the proposed algorithm.

Citation Download Citation

Ali Rostami, Arash Yazdanpanah-Goharrizi, Amin Yazdanpanah-Goharrizi, and F. Janabi-Sharifi "Hybrid neural networks and genetic algorithms for identification of complex Bragg gratings", Proc. SPIE 6374, Optomechatronic Actuators, Manipulation, and Systems Control, 63740W (12 October 2006); https://doi.org/10.1117/12.684880

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KEYWORDS

Fiber Bragg gratings

Genetic algorithms

Neural networks

Optical design

Numerical simulations

Apodization

Neurons

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