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Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations

We propose a description of the model of a random piecewise constant field formed by the sum of realizations of two Markov processes with an arbitrary number of states and defined along mutually perpendicular axes. The number of field quantization levels can be arbitrary. Realizations of a random fi...

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Detalles Bibliográficos
Autores principales: Goritskiy, Yuri, Kazakov, Vladimir, Shevchenko, Olga, Mendoza, Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515321/
https://www.ncbi.nlm.nih.gov/pubmed/33267505
http://dx.doi.org/10.3390/e21080792
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author Goritskiy, Yuri
Kazakov, Vladimir
Shevchenko, Olga
Mendoza, Francisco
author_facet Goritskiy, Yuri
Kazakov, Vladimir
Shevchenko, Olga
Mendoza, Francisco
author_sort Goritskiy, Yuri
collection PubMed
description We propose a description of the model of a random piecewise constant field formed by the sum of realizations of two Markov processes with an arbitrary number of states and defined along mutually perpendicular axes. The number of field quantization levels can be arbitrary. Realizations of a random field model of the desired shape are created by appropriate selection of parameters for formative realization of Markov processes. For the proposed field model, we investigated the sampling and restoration algorithm of any selected realizations. As a result, we determined the optimal sampling and recovery algorithms. The resulting sampling is fundamentally non-periodic. Recovery errors are calculated. Two examples are considered.
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spelling pubmed-75153212020-11-09 Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations Goritskiy, Yuri Kazakov, Vladimir Shevchenko, Olga Mendoza, Francisco Entropy (Basel) Article We propose a description of the model of a random piecewise constant field formed by the sum of realizations of two Markov processes with an arbitrary number of states and defined along mutually perpendicular axes. The number of field quantization levels can be arbitrary. Realizations of a random field model of the desired shape are created by appropriate selection of parameters for formative realization of Markov processes. For the proposed field model, we investigated the sampling and restoration algorithm of any selected realizations. As a result, we determined the optimal sampling and recovery algorithms. The resulting sampling is fundamentally non-periodic. Recovery errors are calculated. Two examples are considered. MDPI 2019-08-14 /pmc/articles/PMC7515321/ /pubmed/33267505 http://dx.doi.org/10.3390/e21080792 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Goritskiy, Yuri
Kazakov, Vladimir
Shevchenko, Olga
Mendoza, Francisco
Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations
title Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations
title_full Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations
title_fullStr Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations
title_full_unstemmed Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations
title_short Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations
title_sort model of random field with piece-constant values and sampling-restoration algorithm of its realizations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515321/
https://www.ncbi.nlm.nih.gov/pubmed/33267505
http://dx.doi.org/10.3390/e21080792
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