Theoretical justification of feasibility to reduce information loss in measurement of continuous random variables in the presence of noise

The article discusses reduction of information loss in measurement of continuous random variables in the presence of noise by the methods of mathematical theory of information. This is important for processing of monitoring data, in particular, methane content of coal mine air during coal production. The process of obtaining information about unknown parameters of gas emissions with the help of gas meters is examined. The model proposed to determine the minimum amount of methane data in case of impairment of measurements is based on the optimization problem solution. The dependence of the methane data quantity on the measurement error probability is found. The accomplished theoretical analysis has found that reduction in information loss needs taking into account the rate of change in the methane measurement information content. The optimized methane control routine is based on a special sequence of sizes of sampling intervals. The change in the criterion of dispersion of epsilon entropy versus distance to the longwall face is determined for the rational layout of methane sensors. The theoretical inferences are confirmed by numerical testing results.

Kupriyanov V.V. Theoretical justification of feasibility to reduce information loss in measurement of continuous random variables in the presence of noise. MIAB. Mining Inf. Anal. Bull. 2021;(8):70-81. [In Russ]. DOI: 10.25018/0236_1493_2021_8_0_70.

V.V. Kupriyanov, Dr. Sci. (Eng.), Professor, National University of Science and Technology «MISiS», 119049, Moscow, Russia, e-mail: msmu_asu@mail.ru.

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