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** Description:** The theoretical basis of the analytical probabilistic modeling of intelligent information-measuring systems is the theory of random processes. The features of the information-measuring systems as objects of modeling, the presence of various converters and elements, the allocation of informative parameters as the basis for the construction of mathematical models and the presentation of the sound characteristics of data arrays require a large amount of research aimed at the development of mathematical, algorithmic and technical support for analytical probabilistic simulation of information-measuring systems. Random processes are described by multi-dimensional probability density distribution laws. We will be talking about stationary random processes that allow with a high enough for most practical cases the probability to describe the steady processes of transforming the informational parameters of the measuring signals in the system. In the article an analysis of the methods for calculating probabilistic characteristics of measuring signals during their transformations in the typical elements of information-measuring systems. Methods for calculating the probabilistic characteristics of measuring signals during their transformations in the type elements of information and measurement systems that can be used as a basis for estimating the distribution of probabilities and corresponding correlation functions in the modeling of typical converters and elements of information-measuring systems are described.

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Keywords:
** information-measuring systems, random processes, metrological characteristics, probabilistic models

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