Yesmagambetov, B.-B. Determination of the Characteristics of Non-Stationary Random Processes by Non-Parametric Methods of Decision Theory. Computation2023, 11, 219.
Yesmagambetov, B.-B. Determination of the Characteristics of Non-Stationary Random Processes by Non-Parametric Methods of Decision Theory. Computation 2023, 11, 219.
Yesmagambetov, B.-B. Determination of the Characteristics of Non-Stationary Random Processes by Non-Parametric Methods of Decision Theory. Computation2023, 11, 219.
Yesmagambetov, B.-B. Determination of the Characteristics of Non-Stationary Random Processes by Non-Parametric Methods of Decision Theory. Computation 2023, 11, 219.
Abstract
This article is devoted to methods of processing random processes. Of particular relevance is the task of processing broadband non-stationary random processes. The processing of random processes is usually related to the assessment of their probabilistic characteristics. Very often, a non-stationary broadband random process is represented by a single implementation in a priori uncertainty about the type of distribution function. Such random processes occur in information and measuring communication systems in which information is transmitted at a real time pace (for example, radio telemetry systems of spacecraft). The use of methods of traditional mathematical statistics, for example, maximum likelihood methods to determine probability characteristics, in this case is not possible. The article discusses a method of processing non-stationary broadband random processes based on the use of non-parametric methods of decision theory. An algorithm for dividing the observation interval into stationary intervals using non-parametric Kendall statistics is considered, as well as methods for estimating probabilistic characteristics on the stationary interval using ordinal statistics. The article presents the results of statistical modeling using the Mathcad program.
Keywords
random process; non-parametric statistics; Kendall statistics; ordinal statistics; stationary interval; probability characteristics
Subject
Computer Science and Mathematics, Computational Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
