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da Silva Ferreira, Adriano; Malheiros-Silveira, Gilliard Nardel; Hernandez-Figueroa, Hugo Enrique
Journal of lightwave technology, 09/2018, Volume: 36, Issue: 18Journal Article
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.
