In paper are considered laws of functioning of discrete determined dynamical systems and specific processes of functioning of such systems. As basic mathematical model of laws of functioning of systems are used automata models with a fundamentally new extension of these models to models with a countable infinite sets of states. This expansion is possible thanks to the proposed and developed by Tverdohlebov V. A. the mathematical apparatus of geometrical images of automaton mappings. Are presented results of development of regularization methods for partially set automata models of systems based on use of geometrical images of automatons mappings and numerical interpolation methods. Also in paper are considered a problem of complexity estimation of laws in a whole and specific processes of functioning of dynamic systems. For these purpose are used recurrent models and methods and also a specific mathematical apparatus of discrete riv-functions. Is spent classification by complexity estimations of automata models.
| Published in | American Journal of Management Science and Engineering (Volume 2, Issue 5) |
| DOI | 10.11648/j.ajmse.20170205.14 |
| Page(s) | 106-116 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2017. Published by Science Publishing Group |
Discrete Dynamical System, Mathematical Model, Automata Model, Geometrical Image of Automaton, Recurrent Model, Interpolation, Discrete Riv-Function
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APA Style
Anton S. Epifanov. (2017). Regularization, Recognition and Complexity Estimation Methods of Automata Models of Discrete Dynamical Systems in Control Problem. American Journal of Management Science and Engineering, 2(5), 106-116. https://doi.org/10.11648/j.ajmse.20170205.14
ACS Style
Anton S. Epifanov. Regularization, Recognition and Complexity Estimation Methods of Automata Models of Discrete Dynamical Systems in Control Problem. Am. J. Manag. Sci. Eng. 2017, 2(5), 106-116. doi: 10.11648/j.ajmse.20170205.14
AMA Style
Anton S. Epifanov. Regularization, Recognition and Complexity Estimation Methods of Automata Models of Discrete Dynamical Systems in Control Problem. Am J Manag Sci Eng. 2017;2(5):106-116. doi: 10.11648/j.ajmse.20170205.14
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Download@article{10.11648/j.ajmse.20170205.14,
author = {Anton S. Epifanov},
title = {Regularization, Recognition and Complexity Estimation Methods of Automata Models of Discrete Dynamical Systems in Control Problem},
journal = {American Journal of Management Science and Engineering},
volume = {2},
number = {5},
pages = {106-116},
doi = {10.11648/j.ajmse.20170205.14},
url = {https://doi.org/10.11648/j.ajmse.20170205.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmse.20170205.14},
abstract = {In paper are considered laws of functioning of discrete determined dynamical systems and specific processes of functioning of such systems. As basic mathematical model of laws of functioning of systems are used automata models with a fundamentally new extension of these models to models with a countable infinite sets of states. This expansion is possible thanks to the proposed and developed by Tverdohlebov V. A. the mathematical apparatus of geometrical images of automaton mappings. Are presented results of development of regularization methods for partially set automata models of systems based on use of geometrical images of automatons mappings and numerical interpolation methods. Also in paper are considered a problem of complexity estimation of laws in a whole and specific processes of functioning of dynamic systems. For these purpose are used recurrent models and methods and also a specific mathematical apparatus of discrete riv-functions. Is spent classification by complexity estimations of automata models.},
year = {2017}
}
TY - JOUR T1 - Regularization, Recognition and Complexity Estimation Methods of Automata Models of Discrete Dynamical Systems in Control Problem AU - Anton S. Epifanov Y1 - 2017/10/23 PY - 2017 N1 - https://doi.org/10.11648/j.ajmse.20170205.14 DO - 10.11648/j.ajmse.20170205.14 T2 - American Journal of Management Science and Engineering JF - American Journal of Management Science and Engineering JO - American Journal of Management Science and Engineering SP - 106 EP - 116 PB - Science Publishing Group SN - 2575-1379 UR - https://doi.org/10.11648/j.ajmse.20170205.14 AB - In paper are considered laws of functioning of discrete determined dynamical systems and specific processes of functioning of such systems. As basic mathematical model of laws of functioning of systems are used automata models with a fundamentally new extension of these models to models with a countable infinite sets of states. This expansion is possible thanks to the proposed and developed by Tverdohlebov V. A. the mathematical apparatus of geometrical images of automaton mappings. Are presented results of development of regularization methods for partially set automata models of systems based on use of geometrical images of automatons mappings and numerical interpolation methods. Also in paper are considered a problem of complexity estimation of laws in a whole and specific processes of functioning of dynamic systems. For these purpose are used recurrent models and methods and also a specific mathematical apparatus of discrete riv-functions. Is spent classification by complexity estimations of automata models. VL - 2 IS - 5 ER -
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