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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: James C. Wyant
  • Vol. 46, Iss. 22 — Aug. 1, 2007
  • pp: 4857–4866

Optics InfoBase > Applied Optics > Volume 46 > Issue 22 > Page 4857

Use of artificial neural networks on optical track width measurements

Richard J. Smith, Chung W. See, Mike G. Somekh, and Andrew Yacoot  »View Author Affiliations


Applied Optics, Vol. 46, Issue 22, pp. 4857-4866 (2007)
http://dx.doi.org/10.1364/AO.46.004857


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Abstract

We have demonstrated recently that, by using an ultrastable optical interferometer together with artificial neural networks (ANNs), track widths down to 60   nm can be measured with a 0.3 NA objective lens. We investigate the effective conditions for training ANNs. Experimental results will be used to show the characteristics of the training samples and the data format of the ANN inputs required to produce suitably trained ANNs. Results obtained with networks measuring double tracks, and classifying different structures, will be presented to illustrate the capability of the technique. We include a discussion on expansion of the application areas of the system, allowing it to be used as a general purpose instrument.

© 2007 Optical Society of America

OCIS Codes
(120.3180) Instrumentation, measurement, and metrology : Interferometry
(120.3940) Instrumentation, measurement, and metrology : Metrology
(120.4640) Instrumentation, measurement, and metrology : Optical instruments
(200.4260) Optics in computing : Neural networks

ToC Category:
Instrumentation, Measurement, and Metrology

History
Original Manuscript: March 20, 2007
Manuscript Accepted: April 17, 2007
Published: June 26, 2007

Citation
Richard J. Smith, Chung W. See, Mike G. Somekh, and Andrew Yacoot, "Use of artificial neural networks on optical track width measurements," Appl. Opt. 46, 4857-4866 (2007)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-46-22-4857

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