ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)

coupling analysis

Selecting time scales for empirical model construction

The task is considered of taking into account the multiple time scales of original time series, with these time series being used for Granger causality estimation. It is proposed to use the combination of prediction length and lag, different in value, that could be fruitful for comparatively short times series, e. g. of medical-biological nature. The automated methods are constructed to select lag and prediction length values. The proposed approach is tested on a set of examples – ethalon systems.

Role of model nonlinearity for granger causality based coupling estimation for pathological tremor

Estimating coupling between systems of different nature is an urgent field of nonlinear dynamics method application. This work aims to compare classical linear Granger approach and its nonlinear analogues based on analysis of ethalon dynamical systems and neurophysiological data. The results achieved show nonlinear approach to be more sensitive, and so it is able to detect significant coupling, when linear one fails.

Diagnostics and correction of systematic error while estimating transfer entropy with k-nearest neighbours method

Transfer entropy is widely used to detect the directed coupling in oscillatory systems from their observed time series. The systematic error is detected, while estimating transfer entropy between nonlinear systems with K-nearest neighbours method. The way to minimize this error is suggested: the error is decreasing with increase of the neighbour number. The possibility to detect the systematic error is shown using two sets of measured data. The achieved results make possible to rise the method sensitivity and specificity for weakly coupled nonlinear systems.