A Neural Network Approach Based on Interference Pattern Analysis: Application to an Autoalignment Method for the Focusing Unit of NFR System
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概要
- 論文の詳細を見る
From the viewpoint of assembly, evaluation results and an autoalignment method for the focusing unit (FU) of a near-field recording (NFR) system are proposed. Generally, the size of the focusing unit composed of the objective lens and the solid immersion lens is smaller than that of the conventional focusing unit. Hence there are difficulties in the precise assembly of the small focusing unit. We developed an evaluation system with an interferometer and evaluated some focusing unit samples, then a tolerance analysis of the assembly error between the SIL and the objective lens and an interference pattern analysis of the assembly error were carried out. A pattern recognition method using a neural network is presented with features, which were extracted from interference patterns due to errors in the FU.
- Published by the Japan Society of Applied Physics through the Institute of Pure and Applied Physicsの論文
- 2004-07-15
著者
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LEE Jun-Hee
NOM Laboratory, Department of Mechanical Engineering, Korea Advanced Institute of Science and Techno
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YOON Hyoung-Kil
NOM Laboratory, Department of Mechanical Engineering, Korea Advanced Institute of Science and Techno
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OH Hyeong-Ryeol
Han-yang University
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Gweon Dae-gab
Nom Laboratary Department Of Mechanical Engineering
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Jeong Jaehwa
NOM Lab., Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-Dong, Yuseong-Gu, ME3265, Daejeon 305-701, Korea
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Yoon Hyoung-Kil
NOM Lab., Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-Dong, Yuseong-Gu, ME3265, Daejeon 305-701, Korea
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Lee Jun-Hee
NOM Lab., Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-Dong, Yuseong-Gu, ME3265, Daejeon 305-701, Korea
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Gweon Dae-Gab
NOM Lab., Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-Dong, Yuseong-Gu, ME3265, Daejeon 305-701, Korea
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