Data resampling: An approach for improving characterization of complex dynamics from noisy interspike intervals
DOI10.1142/S0217979218503356zbMath1423.37037OpenAlexW2904681640WikidataQ128830954 ScholiaQ128830954MaRDI QIDQ5242192
O. N. Pavlova, Alexey N. Pavlov
Publication date: 6 November 2019
Published in: International Journal of Modern Physics B (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1142/s0217979218503356
Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45) Time series analysis of dynamical systems (37M10) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55) Computational methods for ergodic theory (approximation of invariant measures, computation of Lyapunov exponents, entropy, etc.) (37M25)
Cites Work
- Unnamed Item
- A simple model for phase locking of biological oscillators
- Anti-phase, asymmetric and aperiodic oscillations in excitable cells. I: Coupled bursters
- Interspike interval attractors from chaotically driven neuron models
- Improving the quality of extracting dynamics from interspike intervals via a resampling approach
- Quantifying chaotic dynamics from integrate-and-fire processes
- The problem of spurious Lyapunov exponents in time series analysis and its solution by covariant Lyapunov vectors
- LYAPUNOV EXPONENTS IN CHAOTIC SYSTEMS: THEIR IMPORTANCE AND THEIR EVALUATION USING OBSERVED DATA
- IDENTIFICATION OF TRUE AND SPURIOUS LYAPUNOV EXPONENTS FROM TIME SERIES
- An Introduction to the Theory of Point Processes
- Embedding theorems for non-uniformly sampled dynamical systems
- Integrate-and-Fire Models of Nerve Membrane Response to Oscillatory Input
This page was built for publication: Data resampling: An approach for improving characterization of complex dynamics from noisy interspike intervals