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Neural network modeling of Pretilt Angle on the Homogeneous Polyimide Surface

  • 이정환 (연세대학교 전기전자공학과) ;
  • 고영돈 (연세대학교 전기전자공학과) ;
  • 강희진 (연세대학교 전기전자공학과) ;
  • 서대식 (연세대학교 전기전자공학과) ;
  • 윤일구 (연세대학교 전기전자공학과)
  • Lee, Jung-Hwan (Dept. of Electrical and Electronic Engineering, Yonsei University) ;
  • Ko, Young-Don (Dept. of Electrical and Electronic Engineering, Yonsei University) ;
  • Kang, Hee-Jin (Dept. of Electrical and Electronic Engineering, Yonsei University) ;
  • Seo, Dae-Shik (Dept. of Electrical and Electronic Engineering, Yonsei University) ;
  • Yun, Il-Gu (Dept. of Electrical and Electronic Engineering, Yonsei University)
  • 발행 : 2006.06.22

초록

In this paper, the neural network model of the pretilt angle in the nematic liquid crystal on the homogeneous polyimide surface with different surface treatments is investigated. The pretilt angle is one of the main factors to determine the alignment of the liquid crystal display. The pretilt angle is measured to analyze the variation of the characteristics on the various process conditions. The rubbing strength and the hard baking temperature are considered as input factors. Latin hypercube sampling was used to generate initial weights and biases.

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