UDC 519.6
DOI: DOI: 10.36871 / 2618-9976.2021.01.003
Authors
Gorokhov Vladimir Leonidovich
Doctor of technical Sciences, professor Saint Petersburg state Electrotechnical University "LETI",
Saint Petersburg, Russia
Baryshev Yuriy Viktorovich
Doctor of Physical and Mathematical Sciences, Professor of the Department of Astrophysics,
Saint Petersburg State University, Saint Petersburg
Dr. Pekka Teerikorpi
Senior Research Associate at Tuorla Observatory of the Department of Physics and Astronomy
of Turku University
Vitkovsky Vladimir Valentinovich
Candidate of Physical and Mathematical Sciences, Head of the Computer Science Laboratory
of the SAO RAS
Shirokov Stanislav Igorevich
Candidate of Physical and Mathematical Sciences, Researcher of the SAO RAS
Abstract
The article offers an overview and methodology for combining Neumann–Pearson statistics and Bayesian statistics with integrated visualization of cognitive images for processing multidimensional data of astronomical observations. These methods are very successfully applied in astrophysics and can be used for a wide range of problems in BIG DATA. The technique of such a combination can be oriented towards identifying and forecasting emergency situations in complex systems. In the proposed approach, Bayesian integration and visualization of cognitive images is based on the statistical capabilities of algorithms and programs to identify and objectify in cognitive probabilistic images signs of differences in the spatial or temporal structure of objects of observation.
Keywords
Cognitive visualization methods
Multidimensional time series
3D machine graphics
