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Titlebook: Optimization on Low Rank Nonconvex Structures; Hiroshi Konno,Phan Thien Thach,Hoang Tuy Book 1997 Springer Science+Business Media Dordrech

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樓主: 復(fù)雜
11#
發(fā)表于 2025-3-23 12:55:36 | 只看該作者
Hiroshi Konno,Phan Thien Thach,Hoang Tuyy efficient, and stable cooperativity which is governed by universal physical and thermodynamic laws. In this context it is important to realize that synergetics is concerned with processes rather than with reactions; the consideration of forces is replaced by consideration of powers (in the classic
12#
發(fā)表于 2025-3-23 15:44:50 | 只看該作者
Hiroshi Konno,Phan Thien Thach,Hoang Tuyention to this particular state of altered myocardium [7]. Hibernating myocardium, according to Rahimtoola [7, 8] and Braunwald and Rutherford [9], is a state in which chronically reduced myocardial blood flow as a consequence of severe coronary artery disease is associated with an impairment in seg
13#
發(fā)表于 2025-3-23 19:50:19 | 只看該作者
or sudden cardiac death [1, 2]. In this paper we review the coronary angiographic findings in these conditions and speculate as to the pathogenetic differences between syndromes. In particular, we try to answer the question of why a patient develops a particular syndrome following disruption of a p
14#
發(fā)表于 2025-3-24 01:46:47 | 只看該作者
Nonconvex Optimization and Its Applicationshttp://image.papertrans.cn/o/image/703306.jpg
15#
發(fā)表于 2025-3-24 02:22:29 | 只看該作者
https://doi.org/10.1007/978-1-4615-4098-4Optimization algorithm; Optimization algorithms; algorithms; computational geometry; global optimization
16#
發(fā)表于 2025-3-24 07:08:18 | 只看該作者
978-1-4613-6835-9Springer Science+Business Media Dordrecht 1997
17#
發(fā)表于 2025-3-24 14:43:06 | 只看該作者
Optimization on Low Rank Nonconvex Structures978-1-4615-4098-4Series ISSN 1571-568X
18#
發(fā)表于 2025-3-24 17:15:13 | 只看該作者
19#
發(fā)表于 2025-3-24 22:33:01 | 只看該作者
20#
發(fā)表于 2025-3-24 23:59:39 | 只看該作者
Multiplicative Programming ProblemsMultiplicative programming problems are minimization problems containing a product of several convex functions either in its objective function or in its constraints.
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