Topological 3D Model of the Functioning of a Dynamic System – Cognitive Estimation of Complexity
| Authors | V.P. Mygal , G.V. Mygal |
| Affiliations |
National Aerospace University “Kharkiv Aviation Institute”, 17, Chkalova St., 61070 Kharkiv, Ukraine |
| Е-mail | valeriymygal@gmail.com |
| Issue | Volume 13, Year 2021, Number 4 |
| Dates | Received 12 April 2021; revised manuscript received 03 August 2021; published online 20 August 2021 |
| Citation | V.P. Mygal, G.V. Mygal, J. Nano- Electron. Phys. 13 No 4, 04023 (2010) |
| DOI | https://doi.org/10.21272/jnep.13(4).04023 |
| PACS Number(s) | 05.10. – a |
| Keywords | Dynamic complexity, Fractal signals, Hidden structure, Topological models, Spatio-temporal signatures. |
| Annotation |
The article is devoted to the complexity of modeling the functioning of dynamic systems of various nature (sensors, detectors, intelligent materials, and other sources of information). Environmental or activity stressors increase the static complexity of information sources, resulting in dynamic complexity. Information about this is contained in the structure of induced relations, the latent complexity of which limits the ability to predict the functioning of a dynamic system in real time. The purpose of the work is cognitive visualization of the functioning of various sources of information. Morphologically different dynamical systems functionally obey the same extreme principles of physics and are studied by dynamic and statistically methods. Their complementarity made it possible to unify the reconstruction of a three-dimensional (3D) topological model of the functioning of an information source from the measured fractal signal. It was found that the latent structure of the signal is determined by spatial inhomogeneities, which generate temporary inhomogeneities in the information source and transmission environment. Stress factors increase the complexity of spatio-temporal signatures, which makes it possible to estimate the complexity of their configurations by increasing the number of components and the area covered. Therefore, the structure of a fractal signal can be analyzed in real time using additional probabilistic and deterministic methods. The creation of an atlas of fractal signal signatures simplifies the identification and classification of information sources of various nature. Its use will reduce cognitive problems associated with complexity and expand the set of predictive analytics tools. Visualization of latent spatio-temporal features of electrophysiological signals demonstrates the advantages and validity of cognitive visualization of the functioning of different subsystems of the human body. |
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List of References |
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