A particular class of strong non-Markovian stochastic processes have been studied by using a characteristic functional technique previously reported. Exact results for all moments and the whole Kolmogorov hierarchy are presented. The asymptotic scaling of the non-Markovian stochastic process has been characterized in terms of the long-range correlated noise appearing in the correponding stochastic differential equation. A generalized Wiener process has therefore been completely characterized, its power spectrum and fractal dimensions have been studied and its possible connection with the q-statistics has been pointed out
We study steady-state correlation functions of nonlinear stochastic processes driven by external col...
We consider a general class of non-Markovian processes defined by stochastic differential equations ...
The d‐dimentional space‐continuous time‐discrete Markovian random walk with a distribution of step l...
A particular class of strong non-Markovian stochastic processes have been studied by using a charact...
We develop the statistical theory of discrete nonstationary non-Markov random processes in complex s...
For Gaussian processes there is a simple and well-known relationship between the fractal dimension o...
This paper considers the situation where a stochastic process may display both long-range dependence...
We show that the increments of generalized Wiener process, useful to describe non-Gaussian white noi...
The success of current attempts to distinguish between low-dimensional chaos and random behavior in ...
The success of current attempts to distinguish between low-dimensional chaos and random behavior in ...
In this paper we present the concept of description of random processes in complex systems with disc...
This volume collects recent works on weakly dependent, long-memory and multifractal processes and in...
Intermittency is an ubiquitous property of fully developed turbulence, for Eulerian and Lagrangian f...
The exact analytical expression for the Hausdorff dimension of free processes driven by Gaussian noi...
We consider a general class of non-Markovian processes defined by stochastic differential equations ...
We study steady-state correlation functions of nonlinear stochastic processes driven by external col...
We consider a general class of non-Markovian processes defined by stochastic differential equations ...
The d‐dimentional space‐continuous time‐discrete Markovian random walk with a distribution of step l...
A particular class of strong non-Markovian stochastic processes have been studied by using a charact...
We develop the statistical theory of discrete nonstationary non-Markov random processes in complex s...
For Gaussian processes there is a simple and well-known relationship between the fractal dimension o...
This paper considers the situation where a stochastic process may display both long-range dependence...
We show that the increments of generalized Wiener process, useful to describe non-Gaussian white noi...
The success of current attempts to distinguish between low-dimensional chaos and random behavior in ...
The success of current attempts to distinguish between low-dimensional chaos and random behavior in ...
In this paper we present the concept of description of random processes in complex systems with disc...
This volume collects recent works on weakly dependent, long-memory and multifractal processes and in...
Intermittency is an ubiquitous property of fully developed turbulence, for Eulerian and Lagrangian f...
The exact analytical expression for the Hausdorff dimension of free processes driven by Gaussian noi...
We consider a general class of non-Markovian processes defined by stochastic differential equations ...
We study steady-state correlation functions of nonlinear stochastic processes driven by external col...
We consider a general class of non-Markovian processes defined by stochastic differential equations ...
The d‐dimentional space‐continuous time‐discrete Markovian random walk with a distribution of step l...