We propose a method to analyze a turbulent sequence focusing on the self-similar properties of the discrete system it generates. First we show how to approximate the self-similar exponent (ff = 1=3 in the case of hydrodynamic turbulence) from the finite time measurements, and then we establish a criterion to characterize the deviations from asymptotic scaling of the empirical measure generated by finite time sequences. The comparison between an hydrodynamic turbulent sequence and a numerical sequence of Gaussian random variables (which generates a system with self-similarity exponent ff = 1=2), suggests the possibility of a self-similar asymptotic behavior for the system generated by the first one. In the second part of this work, assuming ...
Empirical determination of the scaling properties and exponents of time series presents a formidable...
The purpose of this paper is to study the self-similar properties of discrete-time long memory proce...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....
A scaling hypothesis leading to generalized extended self-similarity (GESS) for velocity structure f...
International audienceBoth theoretical analysis and eddy-damped quasi-normal Markovian (EDQNM) simul...
We study a discrete dissipative dynamical system which presents a transition to turbulence via inter...
Unstably stratified homogeneous turbulence develops at late time a self-similar dynamics characteriz...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
The purpose of this paper is to study the self-similar properties of discrete-time long memory proce...
In statistically stationary conditions, the turbulent energy spectrum in a high Reynolds number flow...
In this paper we report numerical and experimental results on the scaling properties of the velocity...
Decaying turbulence is studied numerically using as initial condition a random flow whose shell-inte...
In the context of fully developed turbulence, Castaing et al. [10] have recently advocated a descrip...
A new self-similarity theory is proposed for decaying two-dimensional Navier–Stokes tur-bulence, inc...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....
Empirical determination of the scaling properties and exponents of time series presents a formidable...
The purpose of this paper is to study the self-similar properties of discrete-time long memory proce...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....
A scaling hypothesis leading to generalized extended self-similarity (GESS) for velocity structure f...
International audienceBoth theoretical analysis and eddy-damped quasi-normal Markovian (EDQNM) simul...
We study a discrete dissipative dynamical system which presents a transition to turbulence via inter...
Unstably stratified homogeneous turbulence develops at late time a self-similar dynamics characteriz...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
The purpose of this paper is to study the self-similar properties of discrete-time long memory proce...
In statistically stationary conditions, the turbulent energy spectrum in a high Reynolds number flow...
In this paper we report numerical and experimental results on the scaling properties of the velocity...
Decaying turbulence is studied numerically using as initial condition a random flow whose shell-inte...
In the context of fully developed turbulence, Castaing et al. [10] have recently advocated a descrip...
A new self-similarity theory is proposed for decaying two-dimensional Navier–Stokes tur-bulence, inc...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....
Empirical determination of the scaling properties and exponents of time series presents a formidable...
The purpose of this paper is to study the self-similar properties of discrete-time long memory proce...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....