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Novel neural network based optimization approach for photonic devices

机译：基于新型神经网络的光子器件优化方法

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摘要

In this paper, a novel optimization technique is proposed for designing photonic devices. The suggested approach relies on the use of radial bases function based artificial neural network (RBF-ANN) which shows an excellent performance in comparison with the conventional artificial neural network technique. The robustness of the suggested RBF-ANN approach is demonstrated through the numerical precision and fast convergence of the design cycle performed on a typical slanted rib waveguide polarization rotator, and ultra-flattened zero dispersion photonic crystal fiber.
机译：本文提出了一种新颖的优化技术，用于设计光子器件。所建议的方法依赖于基于径向基函数的人工神经网络（RBF-ANN）的使用，与传统的人工神经网络技术相比，该算法具有出色的性能。通过在典型的斜肋波导偏振旋转器和超扁平零色散光子晶体光纤上进行的设计周期的数值精度和快速收敛，证明了建议的RBF-ANN方法的鲁棒性。

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  • 来源
    《Optical and quantum electronics》 |2014年第3期|439-453|共15页
  • 作者

    Dalia D. El-Mosalmy; M. F. O. Hameed; Nihal F. F. Areed; S. S. A. Obayya;

  • 作者单位

    Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University,Mansoura, Egypt;

    Centre for Photonics and Smart Materials, Zewail City of Science and Technology, Sheikh Zayed District,6th of October City, Giza, Egypt,Mathematics and Engineering Physics Department, Faculty of Engineering, Mansoura University,Mansoura, Egypt;

    Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University,Mansoura, Egypt,Centre for Photonics and Smart Materials, Zewail City of Science and Technology, Sheikh Zayed District,6th of October City, Giza, Egypt;

    Centre for Photonics and Smart Materials, Zewail City of Science and Technology, Sheikh Zayed District,6th of October City, Giza, Egypt;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Optimization; Artificial neural network; Radial basis function; Polarization rotator; Photonic crystal fiber;

    机译：优化;人工神经网络;径向基函数;偏振旋转器;光子晶体光纤;

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