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Shatskiy, A. A.; Evgeniev, I. Yu., E-mail: shatskiyalex@gmail.com2019
AbstractAbstract
[en] We propose a new method for solving an important problem of astronomy that arises in observations with ultrahigh-angular-resolution interferometers. This method is based on the application of the theory of artificial neural networks. We propose and compute a multiparameter model for a celestial object like Sgr A*. For this model we have numerically constructed a number of probable images for neural network training. After neural network training on these images, the quality of its operation has been tested on another series of images from the same model. We have proven that a neural network can recognize and classify celestial objects (also obtained from interferometers) virtually no worse than can be done by a human.
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Copyright (c) 2019 Pleiades Publishing, Inc.; Country of input: International Atomic Energy Agency (IAEA)
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Journal Article
Journal
Journal of Experimental and Theoretical Physics; ISSN 1063-7761;
; CODEN JTPHES; v. 128(4); p. 592-598

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