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Erschienen in: Measurement Techniques 3/2018

05.07.2018

Filtration of Measurement Data in Structural-Algorithmic Transformations

verfasst von: V. I. Kuznetsov, S. S. Kukushkin

Erschienen in: Measurement Techniques | Ausgabe 3/2018

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Abstract

Results of studies of a nontraditional representation of data images of residues in different variants of their occurrence in word dimensions are presented. The influence of noisy interference on the information content of a sample of telemetry data is investigated. The level of influence of distortions in an implementation of different structures in the formation of transmitted messages is shown. Variant applications of methods of filtration in the solution of problems that arise in processing and analysis of data on the results of measurements are considered. Ways of increasing the temporal density of control of a measurable parameter and decreasing the errors of estimators obtained from an analysis of data on the results of measurements are described and requirements on the carrying capacity of a data transmission channel are presented.

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Literatur
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Zurück zum Zitat S. S. Kukushkin, Theory of Finite Fields and Information, Vol. 1, Methods and Algorithms, Both Classical and Nontraditional Based on the Use of the Constructive Residue Theorem, Ministry of Defense of the Russian Federation, Moscow (2003). S. S. Kukushkin, Theory of Finite Fields and Information, Vol. 1, Methods and Algorithms, Both Classical and Nontraditional Based on the Use of the Constructive Residue Theorem, Ministry of Defense of the Russian Federation, Moscow (2003).
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Zurück zum Zitat V. I. Kuznetsov, “Statistical identification. Adaptive filtration,” Prom. ASU i Kontr., No. 7, 20–27 (2014). V. I. Kuznetsov, “Statistical identification. Adaptive filtration,” Prom. ASU i Kontr., No. 7, 20–27 (2014).
Metadaten
Titel
Filtration of Measurement Data in Structural-Algorithmic Transformations
verfasst von
V. I. Kuznetsov
S. S. Kukushkin
Publikationsdatum
05.07.2018
Verlag
Springer US
Erschienen in
Measurement Techniques / Ausgabe 3/2018
Print ISSN: 0543-1972
Elektronische ISSN: 1573-8906
DOI
https://doi.org/10.1007/s11018-018-1411-8

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