Statistical Complexity as a Criterion for the Useful Signal Detection Problem

Three variants of the statistical complexity function, which is used as a criterion in the problem of detection of a useful signal in the signal-noise mixture, are considered. The probability distributions maximizing the considered variants of statistical complexity are obtained analytically and con...

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Bibliographic Details
Published in:Automation and remote control 2023-07, Vol.84 (7), p.753-771
Main Authors: Galyaev, A. A., Lysenko, P. V., Berlin, L. M.
Format: Article
Language:English
Subjects:
CAE) and Design
Calculus of Variations and Optimal Control
Optimization
Complexity
Computer-Aided Engineering (CAD
Control
Criteria
Mathematical analysis
Mathematics
Mathematics and Statistics
Mechanical Engineering
Mechatronics
Mixtures
Operations Research
Optimization
Robotics
Signal detection
Statistical analysis
System Analysis
Systems Theory
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Summary:Three variants of the statistical complexity function, which is used as a criterion in the problem of detection of a useful signal in the signal-noise mixture, are considered. The probability distributions maximizing the considered variants of statistical complexity are obtained analytically and conclusions about the efficiency of using one or another variant for detection problem are made. The comparison of considered information characteristics is shown and analytical results are illustrated on an example of synthesized signals. A method is proposed for selecting the threshold of the information criterion, which can be used in decision rule for useful signal detection in the signal-noise mixture. The choice of the threshold depends a priori on the analytically obtained maximum values. As a result, the complexity based on the total variation demonstrates the best ability of useful signal detection.
ISSN:0005-1179
1608-3032
DOI:10.1134/S0005117923070056