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Proceedings Paper

Neural network prediction of turbulence-induced wavefront degradations with applications to adaptive optics
Author(s): Mark B. Jorgenson; George J. M. Aitken
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Paper Abstract

Time delays inherent in the control systems of current and proposed adaptive optics systems could be eliminated by predicting atmospherically-distorted wavefronts a short time ahead. An error-backpropagation neural network trained on real astronomical data has demonstrated that time series of wavefront tips and tilts (slopes) in the visible, and piston (displacement) in the infrared, are predictable to a degree which would improve the operation of an adaptive optics telescope.

Paper Details

Date Published: 20 August 1992
PDF: 9 pages
Proc. SPIE 1706, Adaptive and Learning Systems, (20 August 1992); doi: 10.1117/12.139936
Show Author Affiliations
Mark B. Jorgenson, Queen's Univ. (Canada)
George J. M. Aitken, Queen's Univ. (Canada)

Published in SPIE Proceedings Vol. 1706:
Adaptive and Learning Systems
Firooz A. Sadjadi, Editor(s)

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