To appear in Annales Mathématiques Blaise PascalRandom Wavelet Series form a class of random processes with multifractal properties. We give three applications of this construction. First, we synthesize a random function having any given spectrum of singularities satisfying some conditions (but including non-concave spectra). Second, these processes provide examples where the multifractal spectrum coincides with the spectrum of large deviations, and we show how to recover it numerically. Finally, particular cases of these processes satisfy a generalized selfsimilarity relation proposed in the theory of fully developed turbulence
We achieve the multifractal analysis of a class of complex valued statistically self-similar continu...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
We show how wavelet techniques allow to derive irregularity properties of functions on two particula...
We show how wavelet techniques allow to derive irregularity properties of functions on two particula...
We show how wavelet techniques allow to derive irregularity properties of functions on two particula...
International audienceIn this course, we give the basics of the part of multifractal theory that int...
This review presents and compares different multiscale representations, based on either deterministi...
The multifractal formalism for singular measures is revisited using the wavelet transform. For Berno...
International audienceMultivariate multifractal analysis proposes to estimate the multivariate multi...
International audienceMultivariate multifractal analysis proposes to estimate the multivariate multi...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
We achieve the multifractal analysis of a class of complex valued statistically self-similar continu...
We achieve the multifractal analysis of a class of complex valued statistically self-similar continu...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
We show how wavelet techniques allow to derive irregularity properties of functions on two particula...
We show how wavelet techniques allow to derive irregularity properties of functions on two particula...
We show how wavelet techniques allow to derive irregularity properties of functions on two particula...
International audienceIn this course, we give the basics of the part of multifractal theory that int...
This review presents and compares different multiscale representations, based on either deterministi...
The multifractal formalism for singular measures is revisited using the wavelet transform. For Berno...
International audienceMultivariate multifractal analysis proposes to estimate the multivariate multi...
International audienceMultivariate multifractal analysis proposes to estimate the multivariate multi...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
We achieve the multifractal analysis of a class of complex valued statistically self-similar continu...
We achieve the multifractal analysis of a class of complex valued statistically self-similar continu...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...
International audienceThe multifractal formalism for singular measures is revisited using the wavele...