Detrended Flucatuation Analysis (DFA) of Long-range temporal correlations
by Simon-Shlomo Poil
25 Jan 2013
(Updated 31 Jan 2013)
The DFA algorithm is a scaling analysis method used to estimate long-range temporal correlations.
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| Description |
The DFA algorithm is a scaling analysis method used to estimate long-range temporal correlations.
Description: The Detrended flctuation analsysis (DFA) algorithm is a scaling analysis method used to estimate long-range temporal correlations of power-law form. In other words, if a sequence of events has a non-random temporal structure with slowly decaying auto-correlations, DFA can quantify how slowly these correlations decay as indexed by the DFA power-law exponent.
We here present the DFA algorithm implemented as a Biomarker for the Neurophysiological Biomarker Toolbox. You can download this toolbox at http://www.nbtwiki.net.
A tutorial on Detrended fluctuation analysis can be found here: http://www.nbtwiki.net/doku.php?id=tutorial:detrended_fluctuation_analysis_dfa |
| MATLAB release |
MATLAB 7.6 (R2008a)
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| Updates |
| 31 Jan 2013 |
I corrected a missing 'd' in the title |
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