1992

最新文章

• A CHARACTERIZATION OF H-BROWNIAN MOTION BY ITS EXIT DISTRIBUTIONS AI翻译
  作者：VONDRACEK, Z
  摘要：Let X(h) be an h-Brownian motion in the unit ball D subset-of R(d) with h harmonic, such that the representing measure of h is not singular with respect to the surface measure on partial derivative D. If Y is a continuous strong Markov process in D with the same killing distributions as X(h), then Y is a time change of X(h). Similar results hold in simply connected domains in C provided with either the Martin or the Euclidean boundary.
• THE SUBMARTINGALE PROBLEM FOR BROWNIAN-MOTION IN A CONE WITH NONCONSTANT OBLIQUE REFLECTION AI翻译
  作者：KWON, Y
  摘要：This work is concerned with the existence and uniqueness of a strong Markov process that has continuous sample paths and the following additional properties. 1. The state space is a cone in d-dimensions (d greater-than-or-equal-to 3), and the process behaves in the interior of the cone like ordinary Brownian motion. 2. The process reflects instantaneously at the boundary of the cone, the direction of reflection is continuous except at the vertex and has a limit which is fixed on each radial li...
• MAJORIZATION OF GAUSSIAN-PROCESSES AND GEOMETRIC APPLICATIONS AI翻译
  作者：GORDON, Y
  摘要：Let (x(i)*)i = 1n denote the decreasing rearrangement of a sequence of real numbers (x(i))i = 1n. Then for every i not-equal j, and every 1 less-than-or-equal-to k less-than-or-equal-to n, the 2-nd order partial distributional derivatives satisfy the inequality, partial derivative 2/partial derivative x(i) partial derivative x(j) [GRAPHICS] less-than-or-equal-to 0. As a consequence we generalize the theorem due to Fernique and Sudakov. A generalization of Slepian's lemma is also a consequence ...
• LARGE DEVIATIONS FOR THE INVARIANT MEASURE OF A REACTION-DIFFUSION EQUATION WITH NON-GAUSSIAN PERTURBATIONS AI翻译
  作者：SOWERS, R
  作者单位：University of Southern California
  摘要：In this paper we establish a large deviations principle for the invariant measure of the non-Gaussian stochastic partial differential equation (SPDE) partial derivative t-upsilon(epsilon) = L-upsilon(epsilon) + f(x, upsilon(epsilon)) + epsilon-sigma(x, upsilon(epsilon)) W(tx). Here L is a strongly-elliptic second-order operator with constant coefficients, Lh:= DH(xx) - alpha-h, and the space variable x takes values on the unit circle S1. The functions f and sigma are of sufficient regularity t...