Pitfall in Multifractal Analysis of Negative Regularity
Résumé
The recent introduction of p-exponents and p-leaders extends the application of wavelet leader multifractal analysis to functions or signals with negative regularity. These new quantities are defined only for functions that are locally in Lp. However, in practice, estimations from discrete data can always be computed, even if the underlying function that models the data is not in Lp. In this case, the analysis is meaningless but indistinguishable from a valid one. In this contribution, we use a very simple function model provided by deterministic wavelet cascades to study the behavior of multifractal estimates when they are computed from discrete data that is not modeled by a function in Lp, and show that the result is a spectrum with correct shape but shifted so as to exactly be in the Lp limit. We also use numerical simulations on various multifractal random processes to show that the validity of our results extends beyond the simple model that we used.
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