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Titlebook: Inequalities: Theory of Majorization and Its Applications; Albert W. Marshall,Ingram Olkin,Barry C. Arnold Book 2011Latest edition Springe

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21#
發(fā)表于 2025-3-25 05:39:38 | 只看該作者
Albert W. Marshall,Ingram Olkin,Barry C. Arnoldg., turbo and LDPC codes) from a unified pointof view. Since constrained coding is widely used in magnetic andoptical storage, it is necessary to use some special techniques(modified concatenation scheme or bit insertion) in order to applysoft iterative decoding. .Recent breakthroughs in the design
22#
發(fā)表于 2025-3-25 08:30:08 | 只看該作者
Albert W. Marshall,Ingram Olkin,Barry C. Arnoldand LDPC codes) from a unified pointof view. Since constrained coding is widely used in magnetic andoptical storage, it is necessary to use some special techniques(modified concatenation scheme or bit insertion) in order to applysoft iterative decoding. .Recent breakthroughs in the design and decodi
23#
發(fā)表于 2025-3-25 14:23:45 | 只看該作者
978-1-4939-3827-8Springer Science+Business Media, LLC 2011
24#
發(fā)表于 2025-3-25 19:44:12 | 只看該作者
Inequalities: Theory of Majorization and Its Applications978-0-387-68276-1Series ISSN 0172-7397 Series E-ISSN 2197-568X
25#
發(fā)表于 2025-3-25 20:59:07 | 只看該作者
Springer Series in Statisticshttp://image.papertrans.cn/i/image/464398.jpg
26#
發(fā)表于 2025-3-26 04:09:45 | 只看該作者
Introductioncomponents of a vector.. Not surprisingly, the notion 4 arises in a variety of contexts, and it can be made precise in a number 5 of ways. But in remarkably many cases, the appropriate precise state- 6 ment is that “.is majorized by.” (written.and defined ahead 7 in Definition A.1). Some of these cases are reviewed here.
27#
發(fā)表于 2025-3-26 06:36:10 | 只看該作者
28#
發(fā)表于 2025-3-26 11:46:53 | 只看該作者
29#
發(fā)表于 2025-3-26 16:34:04 | 只看該作者
Geometric Inequalitiesgly large. Bottema, Djordjevi?, Jani?, Mitrinovi?, and Vasi? (1969), in their book ., have collected approx- imately 400 inequalities for the triangle. It is shown in this chapter 5 that majorization provides a unified approach to obtaining many known geometric inequalities. This unification also has the advantage of suggesting new inequalities.
30#
發(fā)表于 2025-3-26 20:49:33 | 只看該作者
Numerical Analysistion number and norm of a matrix. Both (i) and (ii) depend on a relation between unitarily invariant norms and symmetric gauge functions (see 3.I.1) obtained by von Neumann (1937). Majorization arises from the fact that symmetric gauge functions are Schur-convex.
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