Journal
JOURNAL OF LIGHTWAVE TECHNOLOGY
Volume 36, Issue 18, Pages 4066-4073Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JLT.2018.2856364
Keywords
Dispersion relation; extreme learning machine; multilayer perceptron; photonic crystal; photonic band gap
Funding
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior
- Conselho Nacional de Desenvolvimento Tecnologico (CNPq) [312110/2016-2]
- Fundacao de Amparo a Pesquisa do Estado de Sao Paulo [2015/24517-8]
- CNPq [300594/2017-8]
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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.
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