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Titlebook: Mathematical Analysis II; Vladimir A. Zorich Textbook 2016Latest edition Springer-Verlag Berlin Heidelberg 2016 calculus.differential equa

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21#
發(fā)表于 2025-3-25 04:27:40 | 只看該作者
*Integration of Differential Forms on Manifolds, derive the contemporary version of the Newton–Leibniz formula, called the general Stokes formula. It incorporates all fundamental classical integral formulas of analysis (Newton–Leibniz, Green, Gauss–Ostrogradskii, and Stokes formulas).
22#
發(fā)表于 2025-3-25 11:07:28 | 只看該作者
Uniform Convergence and the Basic Operations of Analysis on Series and Families of Functions,series, one of the most important technical tools of analysis. We consider different types of convergence of sequences and series of functions, and discuss conditions under which certain useful properties of functions persist after passing to a limit.
23#
發(fā)表于 2025-3-25 11:43:43 | 只看該作者
Integrals Depending on a Parameter,. In this chapter we will study and describe the general properties of integrals depending on a parameter. In particular, we introduce Eulerian integrals and present some basic ideas of generalized functions.
24#
發(fā)表于 2025-3-25 17:32:29 | 只看該作者
25#
發(fā)表于 2025-3-25 20:25:51 | 只看該作者
t years with mutations of the gene SCN4A located in chromosome 17q (23.1 to 25.2) which encodes the α-subunit of the voltage-gated sodium channel of the adult skeletal muscle Barchi 1995; Cannon 1996; George 1995; Hoffman et al. 1995; Lehmann-Horn and Rüidel 1996). The 17 single-point mutations iden
26#
發(fā)表于 2025-3-26 02:10:18 | 只看該作者
27#
發(fā)表于 2025-3-26 05:34:38 | 只看該作者
28#
發(fā)表于 2025-3-26 09:05:44 | 只看該作者
29#
發(fā)表于 2025-3-26 15:12:06 | 只看該作者
Vladimir A. Zorichning and recall performance, and 2) ‘strength of learning’ on the networks’ ability to relearn, or transfer prior learning after aging. In the first experiment dendritic attrition was simulated by random connection pruning and the extent of pruning was progressively increased to simulate aging. In t
30#
發(fā)表于 2025-3-26 18:37:10 | 只看該作者
Vladimir A. Zorichning and recall performance, and 2) ‘strength of learning’ on the networks’ ability to relearn, or transfer prior learning after aging. In the first experiment dendritic attrition was simulated by random connection pruning and the extent of pruning was progressively increased to simulate aging. In t
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