The purpose of this dissertation is to introduce a natural and unifying multifractal formalism which contains the above mentioned multifractal parameters, and gives interesting results for a large class of natural measures. In Part 2 we introduce the proposed multifractal formalism and study it properties. We also show that this multifractal formalism gives natural and interesting results when applied to (nonrandom) graph directed self-similar measures in Rd and "cookie-cutter" measures in R. In Part 3 we use the multifractal formalism introduced in Part 2 to give a detailed discussion of the multifractal structure of random (and hence, as a special case, non-random) graph directed self-similar measures in R^d
AbstractFractals and measures are often defined in a constructive way. In this paper, we give the co...
We establish the validity of the multifractal formalism for random weak Gibbs measures supported on ...
Nous montrons la validité du formalisme multifractal pour les mesures aléatoires faiblement Gibbs po...
AbstractWe define the notion of quasi self-similar measures and show that for such measures their ge...
In this thesis we study the multifractal structure of graph directed self-conformal measures. We beg...
Start with a compact set K ⊂ ℝd . This has a random number of daughter sets, each of which is a (rot...
AbstractClassical multifractal analysis studies the local scaling behaviour of a single measure. How...
Classical multifractal analysis studies the local scaling behaviour of a single measure. However, re...
This is a survey on multifractal analysis with an emphasis on the multifractal geometry of geometric...
Self-similar measures form a fundamental class of fractal measures, and is much less understood if t...
AbstractTo characterize the geometry of a measure, its generalized dimensions dq have been introduce...
AbstractLet X be a metric space and μ a Borel probability measure on X. For q, t ∈ R and E ⊆ X write...
Journal PaperTo characterize the geometry of a measure, its so-called generalized dimensions D(<i>q<...
This thesis explores the relationships between multifractal measures, multiplicative cascades and co...
M. Das proved that the relative multifractal measures are mutually singular for the self-similar mea...
AbstractFractals and measures are often defined in a constructive way. In this paper, we give the co...
We establish the validity of the multifractal formalism for random weak Gibbs measures supported on ...
Nous montrons la validité du formalisme multifractal pour les mesures aléatoires faiblement Gibbs po...
AbstractWe define the notion of quasi self-similar measures and show that for such measures their ge...
In this thesis we study the multifractal structure of graph directed self-conformal measures. We beg...
Start with a compact set K ⊂ ℝd . This has a random number of daughter sets, each of which is a (rot...
AbstractClassical multifractal analysis studies the local scaling behaviour of a single measure. How...
Classical multifractal analysis studies the local scaling behaviour of a single measure. However, re...
This is a survey on multifractal analysis with an emphasis on the multifractal geometry of geometric...
Self-similar measures form a fundamental class of fractal measures, and is much less understood if t...
AbstractTo characterize the geometry of a measure, its generalized dimensions dq have been introduce...
AbstractLet X be a metric space and μ a Borel probability measure on X. For q, t ∈ R and E ⊆ X write...
Journal PaperTo characterize the geometry of a measure, its so-called generalized dimensions D(<i>q<...
This thesis explores the relationships between multifractal measures, multiplicative cascades and co...
M. Das proved that the relative multifractal measures are mutually singular for the self-similar mea...
AbstractFractals and measures are often defined in a constructive way. In this paper, we give the co...
We establish the validity of the multifractal formalism for random weak Gibbs measures supported on ...
Nous montrons la validité du formalisme multifractal pour les mesures aléatoires faiblement Gibbs po...