標(biāo)題: Titlebook: Numerical Optimization with Computational Errors; Alexander J. Zaslavski Book 2016 Springer International Publishing Switzerland 2016 nonl [打印本頁(yè)] 作者: hearing-aid 時(shí)間: 2025-3-21 18:30
書(shū)目名稱(chēng)Numerical Optimization with Computational Errors影響因子(影響力)
書(shū)目名稱(chēng)Numerical Optimization with Computational Errors影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Numerical Optimization with Computational Errors網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Numerical Optimization with Computational Errors網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Numerical Optimization with Computational Errors被引頻次
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書(shū)目名稱(chēng)Numerical Optimization with Computational Errors讀者反饋
書(shū)目名稱(chēng)Numerical Optimization with Computational Errors讀者反饋學(xué)科排名
作者: larder 時(shí)間: 2025-3-21 22:16 作者: MITE 時(shí)間: 2025-3-22 01:20
Alexander J. Zaslavski in these fields contributed review-like chapters about their own work and the work of other researchers to provide a current view of this highly interesting topic..978-3-319-79763-2978-3-319-25301-5Series ISSN 0933-033X Series E-ISSN 2196-2812 作者: 掃興 時(shí)間: 2025-3-22 08:15
Alexander J. Zaslavski in these fields contributed review-like chapters about their own work and the work of other researchers to provide a current view of this highly interesting topic..978-3-319-79763-2978-3-319-25301-5Series ISSN 0933-033X Series E-ISSN 2196-2812 作者: STEER 時(shí)間: 2025-3-22 08:46
Alexander J. Zaslavskiion, or identical dimension) to simplify the problems..This book is attractive for those who look at the deeper aspects of concepts and helps the readerto develop his/her own ideas. In general, it opens a new horizon for improving the existing methods in civil, mechanical, and electrical engineering..978-3-031-12302-3978-3-031-12300-9作者: micronutrients 時(shí)間: 2025-3-22 16:42
1931-6828 felds method, constrained convex minimization problems, the convergence of a proximal point method in a Hilbert space, the continuous subgradient method, penalty methods and Newton’s method. . .??.978-3-319-80917-5978-3-319-30921-7Series ISSN 1931-6828 Series E-ISSN 1931-6836 作者: BOOR 時(shí)間: 2025-3-22 19:33
Alexander J. Zaslavski past four years, the information presented is cutting-edge and comprehensive. As such, the book fills an important gap in the body of literature on the structure of evolution inclusions and its applications..978-981-13-4924-9978-981-10-6656-6Series ISSN 1389-2177 Series E-ISSN 2197-795X 作者: Emasculate 時(shí)間: 2025-3-22 23:41 作者: 大吃大喝 時(shí)間: 2025-3-23 04:17 作者: 平 時(shí)間: 2025-3-23 08:36 作者: 美色花錢(qián) 時(shí)間: 2025-3-23 13:02 作者: Chagrin 時(shí)間: 2025-3-23 16:26
Subgradient Projection Algorithm,onal errors are bounded from above by a small positive constant. Moreover, for a known computational error, we find out what an approximate solution can be obtained and how many iterates one needs for this.作者: Blasphemy 時(shí)間: 2025-3-23 22:02 作者: Indecisive 時(shí)間: 2025-3-23 23:42
1931-6828 tory chapter.Analyzes the gradient projection algorithm for .This book studies the approximate solutions of optimization problems in?the presence of computational errors. A number of results are presented on the?convergence behavior of algorithms in a Hilbert space; these algorithms are examined tak作者: APEX 時(shí)間: 2025-3-24 05:23 作者: Aerophagia 時(shí)間: 2025-3-24 08:19 作者: mortuary 時(shí)間: 2025-3-24 12:32
https://doi.org/10.1007/978-3-319-30921-7nonlinear programming; mathematical programming; proximal point methods; extragradient methods; continuo作者: Ligneous 時(shí)間: 2025-3-24 15:19 作者: modish 時(shí)間: 2025-3-24 22:48
Numerical Optimization with Computational Errors978-3-319-30921-7Series ISSN 1931-6828 Series E-ISSN 1931-6836 作者: 外觀 時(shí)間: 2025-3-24 23:47
Introduction, solution of the problem in the presence of computational errors. We show that the algorithm generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant. In this section we discuss several algorithms which are studied in the book.作者: MAIZE 時(shí)間: 2025-3-25 07:00 作者: dendrites 時(shí)間: 2025-3-25 10:08 作者: forbid 時(shí)間: 2025-3-25 12:16 作者: anaerobic 時(shí)間: 2025-3-25 17:15 作者: CLAMP 時(shí)間: 2025-3-25 22:30 作者: 食品室 時(shí)間: 2025-3-26 01:57
Proximal Point Method in Hilbert Spaces,how the convergence of proximal point methods when computational errors are summable. In this chapter the convergence of the method is established for nonsummable computational errors. We show that the proximal point method generates a good approximate solution if the sequence of computational errors is bounded from above by some constant.作者: perimenopause 時(shí)間: 2025-3-26 04:35 作者: 精致 時(shí)間: 2025-3-26 10:36
Maximal Monotone Operators and the Proximal Point Algorithm,one operator, under the presence of computational errors. The convergence of the method is established for nonsummable computational errors. We show that the proximal point method generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.作者: 婚姻生活 時(shí)間: 2025-3-26 13:46
The Extragradient Method for Solving Variational Inequalities,errors. The convergence of the subgradient method for solving variational inequalities is established for nonsummable computational errors. We show that the subgradient method generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.作者: tenosynovitis 時(shí)間: 2025-3-26 18:54 作者: 古文字學(xué) 時(shí)間: 2025-3-26 22:14
Continuous Subgradient Method,w that our algorithms generate a good approximate solution, if computational errors are bounded from above by a small positive constant. Moreover, for a known computational error, we find out what an approximate solution can be obtained and how much time one needs for this.作者: Malleable 時(shí)間: 2025-3-27 03:06 作者: 小口啜飲 時(shí)間: 2025-3-27 06:58 作者: indicate 時(shí)間: 2025-3-27 11:52
Subgradient Projection Algorithm,f convex–concave functions, under the presence of computational errors. We show that our algorithms generate a good approximate solution, if computational errors are bounded from above by a small positive constant. Moreover, for a known computational error, we find out what an approximate solution c作者: 過(guò)去分詞 時(shí)間: 2025-3-27 14:40
The Mirror Descent Algorithm,erate a good approximate solution, if computational errors are bounded from above by a small positive constant. Moreover, for a known computational error, we find out what an approximate solution can be obtained and how many iterates one needs for this.作者: Thyroid-Gland 時(shí)間: 2025-3-27 19:06
Gradient Algorithm with a Smooth Objective Function,rs. We show that the algorithm generates a good approximate solution, if computational errors are bounded from above by a small positive constant. Moreover, for a known computational error, we find out what an approximate solution can be obtained and how many iterates one needs for this.作者: 紋章 時(shí)間: 2025-3-28 00:49 作者: Cantankerous 時(shí)間: 2025-3-28 03:37 作者: HERE 時(shí)間: 2025-3-28 06:24 作者: 除草劑 時(shí)間: 2025-3-28 11:19 作者: CRUDE 時(shí)間: 2025-3-28 15:16 作者: 匍匐 時(shí)間: 2025-3-28 22:07 作者: avarice 時(shí)間: 2025-3-28 23:25 作者: 聯(lián)邦 時(shí)間: 2025-3-29 06:21
The Extragradient Method for Solving Variational Inequalities,errors. The convergence of the subgradient method for solving variational inequalities is established for nonsummable computational errors. We show that the subgradient method generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.作者: 違抗 時(shí)間: 2025-3-29 09:48 作者: BARGE 時(shí)間: 2025-3-29 13:25
Continuous Subgradient Method,w that our algorithms generate a good approximate solution, if computational errors are bounded from above by a small positive constant. Moreover, for a known computational error, we find out what an approximate solution can be obtained and how much time one needs for this.作者: 芭蕾舞女演員 時(shí)間: 2025-3-29 16:39 作者: Endoscope 時(shí)間: 2025-3-29 22:19
,Newton’s Method,ich appear in the right-hand side of the equations, are not necessarily differentiable. Our goal is to obtain an approximate solution in the presence of computational errors. In order to meet this goal, in the case of inclusions, we study the behavior of iterates of nonexpansive set-valued mappings 作者: Inflammation 時(shí)間: 2025-3-30 02:17 作者: 碌碌之人 時(shí)間: 2025-3-30 06:21
Alexander J. Zaslavskiaccounts, the next generation of supercomputers will achieve its gains by increasing the number of processing elements, rather than by using faster processors. The most difficult technical problem in constructing a supercom- puter will be the design of the interconnection network through which the p作者: Basal-Ganglia 時(shí)間: 2025-3-30 08:47
Alexander J. Zaslavskisions with m-dissipative operators, with the Hille-Yosida op.This book systematically presents the topological structure of solution sets and attractability for nonlinear evolution inclusions, together with its relevant applications in control problems and partial differential equations. It provides作者: 使人入神 時(shí)間: 2025-3-30 14:31 作者: configuration 時(shí)間: 2025-3-30 18:26
Alexander J. Zaslavskiation to domain walls, skyrmions and vortices formed in ferrThis book provides a state-of-the art overview of a highly interesting emerging research field in solid state physics/nanomaterials science,? topological structures in ferroic materials. Topological structures in ferroic materials have rece
