Delay Vector Variance Method

Version 1.0.0.0 (38,2 ko) par Temu
The DVV method for characterisation of time series and signal nonlinearity detection.
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Mise à jour 8 mai 2003

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The Delay Vector Variance (DVV) method characterises a time series in a
standardised way on the basis of its predictability in phase space, by
means of a so-called `DVV-plot'. By itself, these DVV-plots can be
used for time series clustering, as has been shown in Gautama et al.,
2003a for EEG signals. In the context of signal nonlinearity testing,
it can be used in combination with the `surrogate data' method (e.g.,
Schreiber and Schmitz, 2000), namely by characterising the `original'
time series and a number of `surrogates', and statistically testing
whether they are different (Gautama et al., 2003b).

Citation pour cette source

Temu (2026). Delay Vector Variance Method (https://fr.mathworks.com/matlabcentral/fileexchange/3264-delay-vector-variance-method), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R13
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux
Version Publié le Notes de version
1.0.0.0

Corrected a bug (in some situations, the mex file core dumped)