无脊椎
发表于 2025-3-23 10:29:31
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HEW
发表于 2025-3-23 15:01:47
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修正案
发表于 2025-3-23 18:11:44
verges weakly to the unit mass at x.). The study of large deviations is the study of how fast µ. (Γ) → 0 for Γ ∈ . such that x. . Γ̄. In particular, we will be studying situations in which this convergence is exponentially fast and we will be seeking expressions for ..
上下连贯
发表于 2025-3-23 23:07:11
Brian R. Norton,William C. McElligottassume that . is a compact connected Abelian group and that its discrete dual group . has been given some fixed order (B.3). We shall denote the set of nonnegative elements in . with respect to the given order by .. We define the space .(.), 1 ≦ . ≦ ∞, to be the closed ideal in the semi-simple Banac
CODA
发表于 2025-3-24 05:34:22
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Inoperable
发表于 2025-3-24 10:11:20
Brian R. Norton,William C. McElligottlimate by Yu. A. Shishkov and the author (Monin and Shishkov, 1979). Part II of that work gives factual data on climatic changes during the course of the Earth‘978-94-010-8507-6978-94-009-4506-7Series ISSN 1383-8601 Series E-ISSN 2215-162X
的是兄弟
发表于 2025-3-24 12:05:05
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无瑕疵
发表于 2025-3-24 15:49:39
Brian R. Norton,William C. McElligottfirst part of the book the topics covered are mainly fundamental physics. The structure of the atom, considered in non-wave-mechanical terms, leads to the nature of interatomic forces and aggregations of atoms in the three forms-gases, liquids and solids. Sufficient crystallography is discussed to facilitate 978-0-442-30233-7978-94-011-7068-0
退潮
发表于 2025-3-24 22:28:06
Brian R. Norton,William C. McElligott, the well-known Eulerian equations of motion of a solid body about its center of gravity assume the forms . where .. stand for the angular velocities of rotation about the respective axes; and .., for the components of the forces acting on the Moon from outside.
Clinch
发表于 2025-3-25 02:08:22
ous (especially, Gaussian) context, for reasons already touched on in previous chapters: the mean square representations rarely preserve the character of the original trajectories of the process, and the linear predictors to which they give rise can often be improved upon by quite simple nonlinear predictors (cf Chapter 13).