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

有惡臭

指數(shù)

縮影

Small Deviations,ur 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.

interference

可觸知

Examples of Gaussian Random Functions,It was not until the end of the nineteenth century when the chief reason causing such motion has been clarified: a large number of collisions of pollen grains bombarded by molecules of the liquid in their thermal motion. Thus, the phenomenon discovered by Brown has become a visible proof of the “l(fā)if

植物茂盛

cushion

ANTE

Convexity and the Isoperimetric Property, .. In this section, we are going to clarify, in what sense Gaussian distributions are convex. The notion of convexity it related to a remarkable isoperimetric theorem asserting that, among all sets of the same measure, it is the half-space that has the smallest “surface area”. We first consider the

運(yùn)動(dòng)性

Metric Entropy and the Comparison Principle,rds, . may be covered by the balls of radius ε centered at points of .. Denote by . (., ε) the least possible number of points in an ε-. for the set .. Those ε-. which contain exactly . (., ε) points will be called minimal. The quantity . (., ε) ≡ log . (., ε) is called the . of the space ..

chalice