MODELING FROM TIME SERIES AND APPLICATIONS TO PROCESSING OF COMPLEX SIGNALS
Cite this article as:
Bezruchko B. P. MODELING FROM TIME SERIES AND APPLICATIONS TO PROCESSING OF COMPLEX SIGNALS. Izvestiya VUZ. Applied Nonlinear Dynamics, 2009, vol. 17, iss. 5, pp. 70-84. DOI: https://doi.org/10.18500/0869-6632-2009-17-5-70-84
Signals obtained from most of realworld systems, especially from living organisms, are irregular, often chaotic, nonstationary, and noisecorrupted. Since modern measuring devices usually realize digital processing of information, recordings of the signals take the form of a discrete sequence of samples (a time series). The present paper gives a brief overview of the possibilities of such experimental data processing based on reconstruction and usage of a predictive empirical model of a time realization under study. The technique of reconstruction of mathematical models from time series is described and possibilities of the approach are illustrated with examples from the author’s and his colleagues experience.
Изложенные результаты получены в рамках исследований, которые проводились при финансовой поддержке гранта РФФИ (08-02-00081) и Программы Прези- диума РАН «Фундаментальные науки – медицине».
BibTeX
author = {B. P. Bezruchko},
title = {MODELING FROM TIME SERIES AND APPLICATIONS TO PROCESSING OF COMPLEX SIGNALS},
year = {2009},
journal = {Izvestiya VUZ. Applied Nonlinear Dynamics},
volume = {17},number = {5},
url = {https://old-andjournal.sgu.ru/en/articles/modeling-from-time-series-and-applications-to-processing-of-complex-signals},
address = {Саратов},
language = {russian},
doi = {10.18500/0869-6632-2009-17-5-70-84},pages = {70--84},issn = {0869-6632},
keywords = {time series,Signal processing,reconstruction of dynamical systems,coupling diagnostics,empirical modelling,biomedical and geophysical application.},
abstract = {Signals obtained from most of realworld systems, especially from living organisms, are irregular, often chaotic, nonstationary, and noisecorrupted. Since modern measuring devices usually realize digital processing of information, recordings of the signals take the form of a discrete sequence of samples (a time series). The present paper gives a brief overview of the possibilities of such experimental data processing based on reconstruction and usage of a predictive empirical model of a time realization under study. The technique of reconstruction of mathematical models from time series is described and possibilities of the approach are illustrated with examples from the author’s and his colleagues experience. }}