AbstractWe begin with stochastic processes obtained as sums of “up-and-down” pulses with random moments of birth τ and random lifetime w determined by a Poisson random measure. When the pulse amplitude ε → 0, while the pulse density δ increases to infinity, one obtains a process of “fractal sum of micropulses.” A CLT style argument shows convergence in the sense of finite dimensional distributions to a Gaussian process with negatively correlated increments. In the most interesting case the limit is fractional Brownian motion (FBM), a self-affine process with the scaling constant 0 < H < 12. The construction is extended to the multidimensional FBM field as well as to micropulses of more complicated shape
This thesis investigates ruin probabilities and first passage times for self-similar processes. We p...
AbstractWe construct fractional Brownian motion, sub-fractional Brownian motion and negative sub-fra...
28 pages, 9 figuresInternational audienceBrownian motion is the only random process which is Gaussia...
AbstractWe begin with stochastic processes obtained as sums of “up-and-down” pulses with random mome...
AbstractWe showed in an earlier paper (1995a) that negatively correlated fractional Brownian motion ...
We consider the full weak convergence, in appropriate function spaces, of systems of noninteracting ...
We consider the full weak convergence, in appropriate function spaces, of systems of noninteracting ...
Some of the most significant constructions of the fractional brownian motion developed recently are ...
<p>Representation of the continuum of fractal processes, with: the two families of fractional Gaussi...
AbstractThe multifractional Brownian motion (MBM) processes are locally self-similar Gaussian proces...
Fractional Brownian motion (FBM) is a Gaussian stochastic process with stationary, long-time correla...
We study a non-Gaussian and non-stable process arising as the limit of sums of rescaled renewal proc...
Abstract. In this work we introduce correlated random walks on Z. When picking suitably at random th...
Brownian motion, fractional Brownian motion (fBm) and Levy motion are stochastic processes with stat...
Stochastic process exhibiting power-law slopes in the frequency domain are frequently well modeled b...
This thesis investigates ruin probabilities and first passage times for self-similar processes. We p...
AbstractWe construct fractional Brownian motion, sub-fractional Brownian motion and negative sub-fra...
28 pages, 9 figuresInternational audienceBrownian motion is the only random process which is Gaussia...
AbstractWe begin with stochastic processes obtained as sums of “up-and-down” pulses with random mome...
AbstractWe showed in an earlier paper (1995a) that negatively correlated fractional Brownian motion ...
We consider the full weak convergence, in appropriate function spaces, of systems of noninteracting ...
We consider the full weak convergence, in appropriate function spaces, of systems of noninteracting ...
Some of the most significant constructions of the fractional brownian motion developed recently are ...
<p>Representation of the continuum of fractal processes, with: the two families of fractional Gaussi...
AbstractThe multifractional Brownian motion (MBM) processes are locally self-similar Gaussian proces...
Fractional Brownian motion (FBM) is a Gaussian stochastic process with stationary, long-time correla...
We study a non-Gaussian and non-stable process arising as the limit of sums of rescaled renewal proc...
Abstract. In this work we introduce correlated random walks on Z. When picking suitably at random th...
Brownian motion, fractional Brownian motion (fBm) and Levy motion are stochastic processes with stat...
Stochastic process exhibiting power-law slopes in the frequency domain are frequently well modeled b...
This thesis investigates ruin probabilities and first passage times for self-similar processes. We p...
AbstractWe construct fractional Brownian motion, sub-fractional Brownian motion and negative sub-fra...
28 pages, 9 figuresInternational audienceBrownian motion is the only random process which is Gaussia...