20 August 1992 Neural network prediction of turbulence-induced wavefront degradations with applications to adaptive optics
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark B. Jorgenson, Mark B. Jorgenson, George J. M. Aitken, George J. M. Aitken, } "Neural network prediction of turbulence-induced wavefront degradations with applications to adaptive optics", Proc. SPIE 1706, Adaptive and Learning Systems, (20 August 1992); doi: 10.1117/12.139936; https://doi.org/10.1117/12.139936
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