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Titlebook: Gaussian Random Functions; M. A. Lifshits Book 1995 Springer Science+Business Media Dordrecht 1995 Gaussian distribution.Gaussian measure.

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发表于 2025-3-26 21:12:18 | 显示全部楼层
Michel Arock,Gilbert Chemla,Jean-Paul Chemlaur subjects in Section 12. We established that this asymptotics had a unified fashion on the logarithmic level, and this fashion did not depend on the form of A and was controlled by constants governed by the action functional.
发表于 2025-3-27 02:01:15 | 显示全部楼层
,Schweiß- und Schweißrestspannungen,., ρ), and moreover, one can construct an indicator model for this function. The converse is obviously true: If both a Brownian function . an indicator model for this function exist, then (., ρ) may be isometrically embedded into L.. However, a more natural question is the following: Does the existe
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发表于 2025-3-27 09:29:30 | 显示全部楼层
Edward Blair,Kathleen Williamson ξ. If . ⊂ ℝ., the term ‘.’ (or simply .) is used instead of the term ‘random function’; if . ⊂ ℝ., . > 1, the expression ‘.’ is used. In these cases, the elements of . are interpreted as the time instants or space points, respectively. If . = ℕ, a random function ξ is called the ..
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发表于 2025-3-27 23:50:14 | 显示全部楼层
https://doi.org/10.1007/978-94-6091-672-4owever, to a remarkably beautiful result. We shall deal with the typical form of sample functions of a Wiener process which strongly deviate from the (zero) mean. Here, the key part will belong to the isoperimetric inequality and the ellipsoid of concentration, already familiar to the reader.
发表于 2025-3-28 02:31:04 | 显示全部楼层
发表于 2025-3-28 08:21:57 | 显示全部楼层
Random Functions, ξ. If . ⊂ ℝ., the term ‘.’ (or simply .) is used instead of the term ‘random function’; if . ⊂ ℝ., . > 1, the expression ‘.’ is used. In these cases, the elements of . are interpreted as the time instants or space points, respectively. If . = ℕ, a random function ξ is called the ..
发表于 2025-3-28 10:55:39 | 显示全部楼层
The Most Important Gaussian Distributions,e shall consider several measures which are the distributions of the most interesting Gaussian random functions. In each particular situation, we shall find the kernel of the corresponding measure and calculate the action functional and the admissibility rates for shifts.
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