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Open AccessArticle

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

1
Department, Moscow Power Engineering Institute, Technical University, Krasnokazarmennya 14, 111250 Moscow, Russia
2
National Polytechnic Institute of Mexico, Ave. IPN s/n, Building Z, Access 4, 3th Floor, SEPI-Telecommunications, 07738 Mexico City, Mexico
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(8), 792; https://doi.org/10.3390/e21080792
Received: 27 June 2019 / Revised: 31 July 2019 / Accepted: 5 August 2019 / Published: 14 August 2019
(This article belongs to the Section Information Theory, Probability and Statistics)
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Abstract

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. View Full-Text
Keywords: non-gaussian model of a random field with an arbitrary number of states; sampling-reconstruction procedure of such model; reconstruction algorithm; reconstruction error algorithm non-gaussian model of a random field with an arbitrary number of states; sampling-reconstruction procedure of such model; reconstruction algorithm; reconstruction error algorithm
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Goritskiy, Y.; Kazakov, V.; Shevchenko, O.; Mendoza, F. Model of Random Field with Piece-Constant Values and Sampling-Restoration Algorithm of Its Realizations. Entropy 2019, 21, 792.

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