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Estimating mutual information.
TLDR
Two classes of improved estimators for mutual information M(X,Y), from samples of random points distributed according to some joint probability density mu(x,y), based on entropy estimates from k -nearest neighbor distances are presented.
Characterization of Strange Attractors
A new measure of strange attractors is introduced which offers a practical algorithm to determine their character from the time series of a single observable. The relation of this new measure to
Measuring the Strangeness of Strange Attractors
We study the correlation exponent v introduced recently as a characteristic measure of strange attractors which allows one to distinguish between deterministic chaos and random noise. The exponent v
Estimation of the Kolmogorov entropy from a chaotic signal
While there has been recently a dramatic growth in new mathematical concepts related to chaotic systems, ' the detailed comparison between models and experimental data has lagged somewhat. After
Performance of different synchronization measures in real data: a case study on electroencephalographic signals.
TLDR
It is claimed that the applied measures used in the synchronization between left and right hemisphere rat electroencephalographic channels are valuable for the study of synchronization in real data and in the particular case of EEG signals their use as complementary variables could be of clinical relevance.
Toward a quantitative theory of self-generated complexity
TLDR
Quantities are defined operationally which qualify as measures of complexity of patterns arising in physical situations, and are essentially Shannon information needed to specify not individual patterns, but either measure-theoretic or algebraic properties of ensembles of pattern arising ina priori translationally invariant situations.
Event synchronization: a simple and fast method to measure synchronicity and time delay patterns.
TLDR
A simple method to measure synchronization and time-delay patterns between signals, based on the relative timings of events in the time series, which is very simple and fast, thus being suitable for on-line implementations.
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