Scaling features of intermittent dynamics characterized from data sets

Olga N. Pavlova; Alexey N. Pavlov

doi:10.1117/12.2559690

9 April 2020 Scaling features of intermittent dynamics characterized from data sets

Olga N. Pavlova, Alexey N. Pavlov

Proceedings Volume 11459, Saratov Fall Meeting 2019: Computations and Data Analysis: from Nanoscale Tools to Brain Functions; 1145912 (2020) https://doi.org/10.1117/12.2559690
Event: Saratov Fall Meeting 2019: VII International Symposium on Optics and Biophotonics, 2019, Saratov, Russian Federation

Abstract

We discuss how random switching between two states in the dynamics of complex systems affects characterization of oscillations based on data analysis. The appearance of unwanted short segments with distinct correlation features can significantly change the properties of time series estimated by standard numerical methods and, therefore, complicate the diagnosis of the system dynamics. The effects of random switching are much stronger for systems with anti-correlated dynamics compared with the case of power-law correlations.

Citation Download Citation

Olga N. Pavlova and Alexey N. Pavlov "Scaling features of intermittent dynamics characterized from data sets", Proc. SPIE 11459, Saratov Fall Meeting 2019: Computations and Data Analysis: from Nanoscale Tools to Brain Functions, 1145912 (9 April 2020); https://doi.org/10.1117/12.2559690

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