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Optical Engineering

Learning evolution design of multiband-transmission fiber Bragg grating filters
Author(s): Su-Frang Shu; Yin-Chieh Lai; Ci-Ling Pan
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Paper Abstract

A composite fiber Bragg grating (FBG) structure with several apodized sections is utilized for designing dense wavelength division multiplexing (DWDM) multiband transmission filters. A learning genetic algorithm (LGA) is also developed to determine the optimum design parameters of these filters. By taking advantage of a knowledge base (KB) that stores the FBG parameter sets and the corresponding transmission profile feature sets, our LGA can generate a suitable initial population and perform evolutionary optimization starting from it. This has made the LGA evolve more quickly to more accurate results than the methods without using the KB. The LGA can also store new results into the KB according to its decision procedure and improve its precision of initial prediction as it works through more and more examples.

Paper Details

Date Published: 1 October 2003
PDF: 5 pages
Opt. Eng. 42(10) doi: 10.1117/1.1602087
Published in: Optical Engineering Volume 42, Issue 10
Show Author Affiliations
Su-Frang Shu, National Chiao Tung Univ. (Taiwan)
Yin-Chieh Lai, National Chiao-Tung Univ. (Taiwan)
Ci-Ling Pan, National Chiao Tung Univ. (Taiwan)

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