Research of the probability of the "flip" of approximating function during the processing of measurement results

Marchuk, Vladimir; Chernyshov, Dmitry; Sadrtdinov, Ilya; Minaev, Alexander

doi:10.1051/e3sconf/201910402003

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Cited by 4 publications

References 3 publications

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A New Approach to Eliminating the “Flip” Effect of the Approximating Function Under Conditions of a Priori Uncertainty

Marchuk,

Samohleb,

Laouar

et al. 2024

Lecture Notes in Networks and Systems

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A New Approach to Eliminating the “Flip” Effect of the Approximating Function Under Conditions of a Priori Uncertainty

Marchuk,

Samohleb,

Laouar

et al. 2024

Lecture Notes in Networks and Systems

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Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty

et al. 2021

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The paper discusses the issues of practical implementation of increasing the accuracy of signal extraction, which is achieved by eliminating the «flip» of the approximating function when dividing the measured process into intervals under conditions of a priori uncertainty about the signal function, which significantly increases the error of allocating a useful signal. The probability of a «flip» of the approximating function depends significantly on the variance of the additive noise and the sample length. The use of the proposed methods and their software implementation makes it possible to increase the accuracy of the useful signal extraction up to 30 percent in the absence of a priori information about the function of the measured process for complex signals and at least 20% for simpler ones. The use of the proposed methods will significantly increase the processing efficiency in the conditions of a priori uncertainty about the function of the measured process (useful signal) and the statistical characteristics of the additive noise components.

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Comparative analysis of methods for calculating the mode of a stationary random process

et al. 2021

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The paper considers methods for calculating the mode of a stationary random process when solving the problem of processing measurement results under conditions of a priori uncertainty. The results of the conducted studies allowed us to conclude that the most effective method for calculating the mode for a given sample is the proposed method, which allows to increase the accuracy of its calculation by at least 8 times, compared to methods based on the construction of histograms. It should be noted that the proposed method allows to provide an estimate with an error of at least 5% for samples with a number of measurements of about 5 value.

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Research of the probability of the "flip" of approximating function during the processing of measurement results

Cited by 4 publications

References 3 publications

A New Approach to Eliminating the “Flip” Effect of the Approximating Function Under Conditions of a Priori Uncertainty

A New Approach to Eliminating the “Flip” Effect of the Approximating Function Under Conditions of a Priori Uncertainty

Increasing the accuracy of signal extraction by correcting the approximating function under conditions of a priori uncertainty

Comparative analysis of methods for calculating the mode of a stationary random process

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