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J-GLOBAL ID:202002280096387258   Reference number:20A0247732

Recurrent Neural Network for Predicting Dielectric Mirror Reflectivity

誘電体ミラー反射率を予測するためのリカレントニューラルネットワーク
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Volume: 23  Issue:Page: 1012-1018(J-STAGE)  Publication year: 2019 
JST Material Number: F1398A  ISSN: 1343-0130  Document type: Article
Article type: 原著論文  Country of issue: Japan (JPN)  Language: ENGLISH (EN)
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Artificial intelligence  ,  Other optical devices 
Reference (14):
  • [1] P. Baumeister, “Design of Multilayer Filters by Successive Approximations,” J. of the Optical Society of America, Vol.48, Issue 12, pp. 955-958, 1958.
  • [2] R. Szipőcs and A. Kőházi-Kis, “Theory and design of chirped dielectric laser mirrors,” Applied Physics B, Vol.65, Issue 2, pp. 115-135, 1997.
  • [3] Y. Fujimoto et al., “Development on ultra-broadband high intense laser propagation optics for exa-watt laser,” ICUIL, 2012.
  • [4] Y. Gal and Z. Ghahramani, “A theoretically grounded application of dropout in recurrent neural networks,” Proc. of the 30th Int. Conf. on Neural Information Processing Systems (NIPS’16), pp. 1027-1035, 2016.
  • [5] S. Holmes and P. Kraatz, “Investigation of Pulsed CO Laser Damage in Coated Metal Mirrors and Dielectric-Coated Windows,” A. J. Glass and A. H. Guenter (Eds.), “Laser Induced Damage in Optical Materials: 1973,” pp. 138-150, U.S. Department of Commerce and National Bureau of Standards, 1973.
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