Wavefront reconstruction by machine learning using the delta rule

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we use phase screen models to illustrate the power of the delta rule, by obtaining the optimum reconstructor for a Shack-Hartmann sensor with just 6 subapertures in the form of pie segments. The dependence of the matrix elements and residual error on measurement noise is determined, and the accuracy compared with theoretical limits. Reconstructors for more complex problems involving time dependence and multiple laser spots are ideal applications for the method.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsMark A. Ealey, Fritz Merkle
Pages629-635
Number of pages7
Volume2201
StatePublished - 1994
EventAdaptive Optics in Astronomy - Kailua, HI, USA
Duration: Mar 17 1994Mar 18 1994

Other

OtherAdaptive Optics in Astronomy
CityKailua, HI, USA
Period3/17/943/18/94

Fingerprint

machine learning
Wavefronts
noise measurement
time dependence
Learning systems
Lasers
sensors
Sensors
matrices
lasers

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Angel, J. R. P. (1994). Wavefront reconstruction by machine learning using the delta rule. In M. A. Ealey, & F. Merkle (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 2201, pp. 629-635)

Wavefront reconstruction by machine learning using the delta rule. / Angel, J Roger P.

Proceedings of SPIE - The International Society for Optical Engineering. ed. / Mark A. Ealey; Fritz Merkle. Vol. 2201 1994. p. 629-635.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Angel, JRP 1994, Wavefront reconstruction by machine learning using the delta rule. in MA Ealey & F Merkle (eds), Proceedings of SPIE - The International Society for Optical Engineering. vol. 2201, pp. 629-635, Adaptive Optics in Astronomy, Kailua, HI, USA, 3/17/94.
Angel JRP. Wavefront reconstruction by machine learning using the delta rule. In Ealey MA, Merkle F, editors, Proceedings of SPIE - The International Society for Optical Engineering. Vol. 2201. 1994. p. 629-635
Angel, J Roger P. / Wavefront reconstruction by machine learning using the delta rule. Proceedings of SPIE - The International Society for Optical Engineering. editor / Mark A. Ealey ; Fritz Merkle. Vol. 2201 1994. pp. 629-635
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