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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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Název: A neural network approach based on interference pattern analysis: Application to an autoalignment method for the focusing unit of NFR system
Autoři: Yoon, HK, Gweon, Dae-Gab, Lee, JH, Jeong, J, Oh, HR
Přispěvatelé: Gweon, Dae-Gab, Yoon, HK, Lee, JH, Jeong, J, Oh, HR
Informace o vydavateli: Japan Soc Applied Physics
Rok vydání: 2004
Sbírka: Korea Advanced Institute of Science and Technology: KOASAS - KAIST Open Access Self-Archiving System
Témata: DATA-STORAGE, LENS, solid immersion lens, near-field recording, interference pattern analysis, neural network, pattern recognition, autoalignment method
Popis: 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.
Druh dokumentu: article in journal/newspaper
Jazyk: English
Relation: http://hdl.handle.net/10203/84895; 596; 67073; 000223477600075
Dostupnost: http://hdl.handle.net/10203/84895
Přístupové číslo: edsbas.56FF23BF
Databáze: BASE
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: A neural network approach based on interference pattern analysis: Application to an autoalignment method for the focusing unit of NFR system
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Yoon%2C+HK%22">Yoon, HK</searchLink><br /><searchLink fieldCode="AR" term="%22Gweon%2C+Dae-Gab%22">Gweon, Dae-Gab</searchLink><br /><searchLink fieldCode="AR" term="%22Lee%2C+JH%22">Lee, JH</searchLink><br /><searchLink fieldCode="AR" term="%22Jeong%2C+J%22">Jeong, J</searchLink><br /><searchLink fieldCode="AR" term="%22Oh%2C+HR%22">Oh, HR</searchLink>
– Name: Author
  Label: Contributors
  Group: Au
  Data: Gweon, Dae-Gab<br />Yoon, HK<br />Lee, JH<br />Jeong, J<br />Oh, HR
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: Japan Soc Applied Physics
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2004
– Name: Subset
  Label: Collection
  Group: HoldingsInfo
  Data: Korea Advanced Institute of Science and Technology: KOASAS - KAIST Open Access Self-Archiving System
– Name: Subject
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  Group: Su
  Data: <searchLink fieldCode="DE" term="%22DATA-STORAGE%22">DATA-STORAGE</searchLink><br /><searchLink fieldCode="DE" term="%22LENS%22">LENS</searchLink><br /><searchLink fieldCode="DE" term="%22solid+immersion+lens%22">solid immersion lens</searchLink><br /><searchLink fieldCode="DE" term="%22near-field+recording%22">near-field recording</searchLink><br /><searchLink fieldCode="DE" term="%22interference+pattern+analysis%22">interference pattern analysis</searchLink><br /><searchLink fieldCode="DE" term="%22neural+network%22">neural network</searchLink><br /><searchLink fieldCode="DE" term="%22pattern+recognition%22">pattern recognition</searchLink><br /><searchLink fieldCode="DE" term="%22autoalignment+method%22">autoalignment method</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: 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.
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  Data: article in journal/newspaper
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  Data: English
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  Data: http://hdl.handle.net/10203/84895; 596; 67073; 000223477600075
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  Data: http://hdl.handle.net/10203/84895
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  Data: edsbas.56FF23BF
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    Subjects:
      – SubjectFull: DATA-STORAGE
        Type: general
      – SubjectFull: LENS
        Type: general
      – SubjectFull: solid immersion lens
        Type: general
      – SubjectFull: near-field recording
        Type: general
      – SubjectFull: interference pattern analysis
        Type: general
      – SubjectFull: neural network
        Type: general
      – SubjectFull: pattern recognition
        Type: general
      – SubjectFull: autoalignment method
        Type: general
    Titles:
      – TitleFull: 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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            NameFull: Yoon, HK
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            NameFull: Lee, JH
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              M: 01
              Type: published
              Y: 2004
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