Investigation of the Window Variance Noise Component of Multicomponent Signals
- Authors: Dranitsyna M.A.1, Zakharova T.1,2
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Affiliations:
- Lomonosov Moscow State University
- Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences
- Issue: Vol 237, No 5 (2019)
- Pages: 639-645
- Section: Article
- URL: https://journals.rcsi.science/1072-3374/article/view/242417
- DOI: https://doi.org/10.1007/s10958-019-04189-x
- ID: 242417
Cite item
Abstract
Signal partitioning or signal segmentation allows to perform data classification, prediction of signals’ behavior, and profound interpretation of obtained data. In accordance with the signal model some distribution characteristics of the window variance noise component are investigated. It was shown that when all true underlying signal components remain unchanged, the window variance noise component is gamma distributed. Applying window variance to multicomponent signal (i.e., pharmacokinetic curve), it was shown that the window variance allows to split visually the signal record into phases due to prevalent processes.
About the authors
M. A. Dranitsyna
Lomonosov Moscow State University
Author for correspondence.
Email: margarita13april@mail.ru
Russian Federation, Moscow
T.V. Zakharova
Lomonosov Moscow State University; Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences
Email: margarita13april@mail.ru
Russian Federation, Moscow; Moscow