Abstract
The article is devoted to the analysis of the problem of correction of atmospheric turbulence distortions by means of adaptive optics and neural network approaches to its solution. The problem is characterized, the main currently used methods of solving it are described, and the goal is to develop a method based on machine learning algorithms aimed at correcting distortions that occur during the passage of a wavefront through atmospheric turbulence using adaptive optics. Possible neural network approaches to achieve the goal using different neural network architectures are considered. The proposed method of using such approaches in solving the highlighted problem is described. The advantages and disadvantages of different approaches are compared. Based on the analysis, a software architecture is proposed for a prototype of an adaptive optics control system based on neural network technologies.
Published Version
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