31 May 1994 Wavefront reconstruction by machine learning using the delta rule
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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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James Roger P. Angel, "Wavefront reconstruction by machine learning using the delta rule", Proc. SPIE 2201, Adaptive Optics in Astronomy, (31 May 1994); doi: 10.1117/12.176098; https://doi.org/10.1117/12.176098
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