39 research outputs found
A strong invariance principle for associated random fields
In this paper we generalize Yu's [Ann. Probab. 24 (1996) 2079-2097] strong
invariance principle for associated sequences to the multi-parameter case,
under the assumption that the covariance coefficient u(n) decays exponentially
as n\to \infty. The main tools that we use are the following: the Berkes and
Morrow [Z. Wahrsch. Verw. Gebiete 57 (1981) 15-37] multi-parameter blocking
technique, the Csorgo and Revesz [Z. Wahrsch. Verw. Gebiete 31 (1975) 255-260]
quantile transform method and the Bulinski [Theory Probab. Appl. 40 (1995)
136-144] rate of convergence in the CLT.Comment: Published at http://dx.doi.org/10.1214/009117904000001071 in the
Annals of Probability (http://www.imstat.org/aop/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Linear SPDEs with harmonizable noise
Using tools from the theory of random fields with stationary increments, we
introduce a new class of processes which can be used as a model for the noise
perturbing an SPDE. This type of noise (called harmonizable) is not necessarily
Gaussian, but it includes the spatially homogeneous Gaussian noise introduced
in Dalang (1999), and the fractional noise considered in Balan and Tudor
(2010). We derive some general conditions for the existence of a random field
solution of a linear SPDE with harmonizable noise, under some mild conditions
imposed on the Green function of the differential operator which appears in
this equation. This methodology is applied to the study of the heat and wave
equations (possibly replacing the Laplacian by one of its fractional powers),
extending in this manner the results of Balan and Tudor (2010) to the case
.Comment: 31 page
The Stochastic Heat Equation with a Fractional-Colored Noise: Existence of the Solution
In this article we consider the stochastic heat equation in (0,T) \times \bR^d, with vanishing initial conditions, driven by a
Gaussian noise which is fractional in time, with Hurst index , and colored in space, with spatial covariance given by a function
. Our main result gives the necessary and sufficient condition on for
the existence of the process solution. When is the Riesz kernel of order
this condition is , which is a relaxation of
the condition encountered when the noise is white in space.
When is the Bessel kernel or the heat kernel, the condition remains