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Proceedings Paper

Reconstruction of dynamical systems from resampled point processes produced by neuron models
Author(s): Olga N. Pavlova; Alexey N. Pavlov
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Paper Abstract

Characterization of dynamical features of chaotic oscillations from point processes is based on embedding theorems for non-uniformly sampled signals such as the sequences of interspike intervals (ISIs). This theoretical background confirms the ability of attractor reconstruction from ISIs generated by chaotically driven neuron models. The quality of such reconstruction depends on the available length of the analyzed dataset. We discuss how data resampling improves the reconstruction for short amount of data and show that this effect is observed for different types of mechanisms for spike generation.

Paper Details

Date Published: 26 April 2018
PDF: 6 pages
Proc. SPIE 10717, Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV, 107171Q (26 April 2018); doi: 10.1117/12.2309626
Show Author Affiliations
Olga N. Pavlova, Saratov State Univ. (Russian Federation)
Alexey N. Pavlov, Yuri Gagarin State Technical Univ. of Saratov (Russian Federation)
Saratov State Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 10717:
Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV
Vladimir L. Derbov; Dmitry Engelevich Postnov, Editor(s)

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