Results 31 to 40 of about 31,033 (265)
Lyapunov exponent using Euler’s algorithm with applications in optimization problems [PDF]
Yugoslav Journal of Operations Research, 2022 The difference and differential equations have played an eminent part in nonlinear dynamics systems, but in the last two decades one-dimensional difference maps are considered in the forefront of nonlinear systems and the optimization of ...
Ashish +4 more
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A distance-based dynamical transition analysis of time series signals and application to biological systems [PDF]
Journal of Biological Physics, 2011 This study demonstrates an application of distance-based numerical measures to the phase space of time series signals, in order to obtain a temporal analysis of complex dynamical systems. This method is capable of detecting alterations appearing in the characters of the deterministic dynamical systems and provides a simple tool for the real-time ...
Serkan, Alagoz, Baris Baykant, Alagoz
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The frequency of pattern occurrence in random walks [PDF]
Discrete Mathematics & Theoretical Computer Science, 2015 In the past decade, the use of ordinal patterns in the analysis of time series and dynamical systems has become an important tool. Ordinal patterns (otherwise known as a permutation patterns) are found in time series by taking $n$ data points at evenly ...
Sergi Elizalde, Megan Martinez
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Nonstationary time-series analysis applied to investigation of brainstem system dynamics
IEEE Transactions on Biomedical Engineering, 2000 Previous investigations of the dynamic organization of the lower brainstem and its relation to peripheral and other central nervous systems were predominantly performed by linear methods. These are based on time-averaging algorithms, which merely can be applied to stationary signal intervals.
Vandenhouten, Ralf +3 more
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Transform-Based Multilinear Dynamical System for Tensor Time Series Analysis
CoRR, 2018 We propose a novel multilinear dynamical system (MLDS) in a transform domain, named $\mathcal{L}$-MLDS, to model tensor time series. With transformations applied to a tensor data, the latent multidimensional correlations among the frontal slices are built, and thus resulting in the computational independence in the transform domain.
Weijun Lu +4 more
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PLoS Computational Biology, 2019 A major tenet in theoretical neuroscience is that cognitive and behavioral processes are ultimately implemented in terms of the neural system dynamics.
Georgia Koppe +4 more
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Combining global and multi-scale features in a description of the solar wind-magnetosphere coupling [PDF]
Annales Geophysicae, 2003 The solar wind-magnetosphere coupling during substorms exhibits dynamical features in a wide range of spatial and temporal scales. The goal of our work is to combine the global and multi-scale description of magnetospheric dynamics in a unified ...
A. Y. Ukhorskiy +4 more
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NoLiTiA: An Open-Source Toolbox for Non-linear Time Series Analysis
Frontiers in Neuroinformatics, 2022 In many scientific fields including neuroscience, climatology or physics, complex relationships can be described most parsimoniously by non-linear mechanics.
Immo Weber +2 more
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Entropy Analysis of High-Definition Transcranial Electric Stimulation Effects on EEG Dynamics
Brain Sciences, 2019 A foundation of medical research is time series analysis—the behavior of variables of interest with respect to time. Time series data are often analyzed using the mean, with statistical tests applied to mean differences, and has the assumption that
Diego C. Nascimento +7 more
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Time Series Analysis Process of Dynamic Data in Internet of Things System
Journal of Physics: Conference Series, 2021 Abstract Time series analysis is a dynamic data analysis and processing method. The biggest characteristic of time series analysis is that the successive observations are not independent. When the observation series are correlated, the autocorrelation between the observation data can be used to establish the dynamic model of the data ...
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