Add to ORKGA stochastic process Y (t) is defined as self-similar with self-similarity parameter H if for any positive stretching factor c, the distribution of the rescaled and reindexed process c−H Y (c t) is equivalent to that of the original process Y (t). This means for any sequence of time points t1,..., tn and any positive constant c, the collections {c−H Y (c t1),..., c−H Y (ctn)
We investigate the performance of wavelet shrinkage methods for the denoising of symmetric-a-stable ...
AbstractA stochastic process on a finite-dimensional real vector space is operator-self-similar if a...
In the last years fractal models have become the focus of many contributions dealing with market dyn...
A stochastic process Y (t) is dened as self-similar with self-similarity parameter H if for any posi...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
By using chaos expansion into multiple stochastic integrals, we make a wavelet analysis of two self-...
This work is concerned with the analysis of self-similar stochastic pro-cesses, where statistical se...
International audienceBy using chaos expansion into multiple stochastic integrals, we make a wavelet...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
Statistical analysis and synthesis of self-similar discrete time signals are presented. The analysis...
Abstract: This note surveys some recent results on self-similar Markov processes. Since the research...
We study the concept of self-similarity with respect to stochastic time change. The negative binomia...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
Statistical self-similarity of random processes in continuous-domains is defined through invariance ...
We investigate the performance of wavelet shrinkage methods for the denoising of symmetric-a-stable ...
AbstractA stochastic process on a finite-dimensional real vector space is operator-self-similar if a...
In the last years fractal models have become the focus of many contributions dealing with market dyn...
A stochastic process Y (t) is dened as self-similar with self-similarity parameter H if for any posi...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
By using chaos expansion into multiple stochastic integrals, we make a wavelet analysis of two self-...
This work is concerned with the analysis of self-similar stochastic pro-cesses, where statistical se...
International audienceBy using chaos expansion into multiple stochastic integrals, we make a wavelet...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
Statistical analysis and synthesis of self-similar discrete time signals are presented. The analysis...
Abstract: This note surveys some recent results on self-similar Markov processes. Since the research...
We study the concept of self-similarity with respect to stochastic time change. The negative binomia...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
Statistical self-similarity of random processes in continuous-domains is defined through invariance ...
We investigate the performance of wavelet shrinkage methods for the denoising of symmetric-a-stable ...
AbstractA stochastic process on a finite-dimensional real vector space is operator-self-similar if a...
In the last years fractal models have become the focus of many contributions dealing with market dyn...