Title
Computing Optical Properties of Photonic Crystals by Using Multilayer Perceptron and Extreme Learning Machine
Date Issued
15 September 2018
Access level
open access
Resource Type
journal article
Author(s)
Universidad Estatal de Campinas
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
In this paper, dispersion relations (DRs) of photonic crystals (PhCs) are computed by multilayer perceptron (MLP) and extreme learning machine (ELM) artificial neural networks (ANNs). Bi- and tri-dimensional optimized structures presenting distinct DRs and photonic band gaps (PBGs) were selected for case studies. Optical properties of a set of PhCs with similar geometries and different dimensions were calculated by an electromagnetic solver in order to provide input data for ANN training and testing. We demonstrate that simple- and fast-training ANN models are capable of providing accurate DRs' curves in a very short time.
Start page
4066
End page
4073
Volume
36
Issue
18
Language
English
OCDE Knowledge area
Ingeniería eléctrica, Ingeniería electrónica
Hardware, Arquitectura de computadoras
Subjects
Scopus EID
2-s2.0-85049998933
Source
Journal of Lightwave Technology
ISSN of the container
07338724
Sponsor(s)
Manuscript received April 8, 2018; revised July 4, 2018; accepted July 9, 2018. Date of publication July 16, 2018; date of current version August 6, 2018. The work of A. da Silva Ferreira and H. E. Hernández-Figueroa was supported in part by the Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nível Superior, in part by the Conselho Nacional de Desenvolvimento Tecnológico (CNPq) under Grant #312110/2016-2, and in part by the Fundac¸ão de Amparo à Pesquisa do Estado de São Paulo under Project 2015/24517-8. The work of G. N. Malheiros-Silveira was supported by CNPq under Grant #300594/2017-8. (Corresponding author: Adriano da Silva Ferreira.) A. da Silva Ferreira and H. E. Hernández-Figueroa are with the School of Electrical and Computer Engineering, University of Campinas, Campinas SP 13083-852, Brazil (e-mail:, adrianof@decom.fee.unicamp.br; hugo@decom.fee.unicamp.br).
The work of A. da Silva Ferreira and H. E. Hern?ndez-Figueroa was supported in part by the Coordena? ?o de Aperfei?oamento de Pessoal de N?vel Superior, in part by the Conselho Nacional de Desenvolvimento Tecnologico (CNPq) under Grant #312110/2016-2, and in part by the Funda? ?o de Amparo a Pesquisa do Estado de S?o Paulo under Project 2015/24517-8. The work of G. N. Malheiros-Silveira was supported by CNPq under Grant #300594/2017-8.
Sources of information:
Directorio de Producción Científica
Scopus