Results 151 to 160 of about 1,170,059 (167)

Occupation Density and Sample Path Properties

2003
0 Introduction 0.1 Gaussian (N, d)-fields 0.2 (\(N,d, \alpha\))-stable Levy sheets 0.3 Other fields 1 Occupation density of a function and the Hausdorff dimension of its level sets 1.1 Occupation density of a function 1.2 Holder continuity and Hausdorff dimension 1.A Fourier transform of multivariate measures
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Dimension properties of sample paths of self-similar processes

Acta Mathematica Sinica, 1994
The Hausdorff dimensions of the image \(X(t)\), \(t \in E \subset R^ N\), \(N \geq 1\), and the graph \(\text{Gr }X(E) = \{(t,X(t)), t \in E\}\) are found out for the random fields with independent components. The results are extended to self-similar processes and fields (also vector-valued) with stationary increments, including Brownian motion ...
Xiao, Yimin, Lin, Huonan
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On the sample path properties of mixed Poisson processes

Operations Research Letters, 2018
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Fu, Miaoqi MATH, Peng, Xianhua
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Sample path properties of stochastic integrals, and stochastic differentiation

Stochastics and Stochastic Reports, 1989
Let B be a Brownian motion, and X = H.B be a stochastic integral of B. We give conditions on the smoothness of the process H which imply that if Ms a singular point of the sample path of B (ω) (such as a local maximum, a slow point, or a fast point) then t is also a singular point of X (ω).
Martin T. Barlow, Edwin A. Perkins
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Sample Path Properties of Stable Processes

Technometrics, 1982
R. Syski, J. L. Mijnheer, H. C. P. Berbee, P. J. M. Kallenberg   +3 more
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Sample Path Properties of Gaussian Invariant Random Fields

2013
Let X(t) be a centred Gaussian invariant random field on a two-point homogeneous space T. The corresponding Dudley semi-metric is a function of one real variable. We use Abelian and Tauberian theorems to estimate the Dudley semi-metric and find the uniform moduli of continuity of the random field X(t).
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Gaussian Signals, Covariance Matrices, and Sample Path Properties

2010
In general, determining the shape of the sample paths of a random signal X(t) requires knowledge of n-D (or, in the terminology of signal processing, n-point) probabilities $$P\left(a_{1} < X(t_{1})
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Sample Path Properties

2013
Björn Böttcher, René Schilling, Jian Wang   +2 more
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Introduction to sample path properties

2017
Gennady Samorodnitsky, Murad S. Taqqu
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TWO SAMPLE PATH PROPERTIES ON VOLTERRA PROCESSES

Far East Journal of Mathematical Sciences (FJMS), 2018
Sun Qiaoge, Xie Yuquan, Su Rong Su Rong
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