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MULTIFRACS is the French ANR grant ANR-16-CE33-0020.
January 2017 - June 2020
MULTIFRACS is the French ANR grant ANR-16-CE33-0020.
January 2017 - June 2020
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It shows that that scale-free temporal dynamics in brain activity (recorded by MEG) are modulated from rest to task as a significant and global decrease of selfsimilarity with a reinforcement of a fronto-occipital gradient, accompanied by a significant increase of multifractality localized in regions engaged in the task.
has been made available on the Multifractal Website.
It proposes a the first procedure to estimate self-similarity parameters in M-components multivariate time series and studies theoretically and practically its statistical performance.
It proposes a Bayesian model for the joint estimation for multifractal parameters for multivariate time series and images.
It investigates the interest, difficulties and (counter)-intuitions in defining multivariate multifractal analysis
Herwig Wendt of the Toulouse team received the Early Career Award of the European Association for Signal Processing (EURASIP) for ''Significant Contributions to Statistical Inference in Multivariate Multidimensional Multifractal Analysis''.
The ANR project MULTIFRACS has been officially launched 25-27 January 2017 at IRIT laboratory, CNRS UMR 5505, Toulouse.