Abstract
We explore the capabilities of multiresolution wavelet analysis (MWA) to characterize complex dynamics based on short data sets that can be applied for diagnosing inter-state transitions. Using the example of chaos–hyperchaos transitions in the model of two interacting Rössler systems, we establish the minimum amount of data necessary for reliable separation of chaotic and hyperchaotic oscillations and discuss how this amount changes depending on the length of the transient process. We then discuss transitions between wakefulness and artificial sleep in mice and estimate the duration of electroencephalograms (EEG) that provide separation between these states.
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Acknowledgements
This work was supported by the Russian Science Foundation (Agreement 19-12-00037) in the part of the theoretical and numerical studies. Physiological experiments described in Sects. 2.3 and 3.2 were carried out within the framework of the grant from the Government of the Russian Federation No. 075-15-2022-1094.
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Guyo, G.A., Pavlova, O.N., Blokhina, I.A. et al. Multiresolution wavelet analysis of transients: numerical simulations and application to EEG. Eur. Phys. J. Spec. Top. 232, 635–641 (2023). https://doi.org/10.1140/epjs/s11734-022-00710-7
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DOI: https://doi.org/10.1140/epjs/s11734-022-00710-7