標(biāo)題: Titlebook: Best Approximation in Inner Product Spaces; Frank Deutsch Textbook 2001 Springer-Verlag New York 2001 Convexity.Hilbert space.algorithms.c [打印本頁] 作者: 分類 時間: 2025-3-21 19:08
書目名稱Best Approximation in Inner Product Spaces影響因子(影響力)
書目名稱Best Approximation in Inner Product Spaces影響因子(影響力)學(xué)科排名
書目名稱Best Approximation in Inner Product Spaces網(wǎng)絡(luò)公開度
書目名稱Best Approximation in Inner Product Spaces網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Best Approximation in Inner Product Spaces被引頻次
書目名稱Best Approximation in Inner Product Spaces被引頻次學(xué)科排名
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書目名稱Best Approximation in Inner Product Spaces年度引用學(xué)科排名
書目名稱Best Approximation in Inner Product Spaces讀者反饋
書目名稱Best Approximation in Inner Product Spaces讀者反饋學(xué)科排名
作者: sacrum 時間: 2025-3-21 23:28
Existence and Uniqueness of Best Approximations,ce theorems of interest. In particular, the two most useful existence and uniqueness theorems can be deduced from it. They are: (1) Every finite-dimensional subspace is Chebyshev, and (2) every closed convex subset of a Hilbert space is Chebyshev.作者: 名字的誤用 時間: 2025-3-22 01:30
Characterization of Best Approximations,deed, it will be the basis for . characterization theorem that we give. The notion of a dual cone plays an essential role in this characterization. In the particular case where the convex set is a subspace, we obtain the familiar orthogonality condition, which for finite-dimensional subspaces reduce作者: Malleable 時間: 2025-3-22 07:29 作者: 小說 時間: 2025-3-22 11:01
Bounded Linear Functionals and Best Approximation from Hyperplanes and Half-Spaces,subspaces, these functionals are the most important linear mappings that arise in our work. We saw in the last chapter that every element of the inner product space . naturally generates a bounded linear functional on . (see Theorem 5.18). Here we give a general representation theorem for . bounded 作者: concentrate 時間: 2025-3-22 14:53
Error of Approximation, given an explicit formula for the distance . in the last chapter (Theorem 6.25), and a strengthening of this distance formula in the particular case where the convex set . is either a convex cone or a subspace (Theorem 6.26). Now we will extract still further refinements, improvements, and applicat作者: 臭名昭著 時間: 2025-3-22 17:36 作者: 無孔 時間: 2025-3-22 22:38
Interpolation and Approximation,terpolation (SAI), simultaneous approximation and norm-preservation (SAN), simultaneous interpolation and norm-preservation (SIN), and simultaneous approximation and interpolation with norm-preservation (SAIN).作者: craven 時間: 2025-3-23 05:20 作者: 高度表 時間: 2025-3-23 05:45 作者: 反應(yīng) 時間: 2025-3-23 12:50 作者: Delude 時間: 2025-3-23 16:58
The Method of Alternating Projections,ety of problems including solving linear equations, solving linear inequalities, computing the best isotone and best convex regression functions, and solving the general shape-preserving interpolation problem.作者: 散步 時間: 2025-3-23 18:54 作者: 不可救藥 時間: 2025-3-24 01:19 作者: ethnology 時間: 2025-3-24 06:07 作者: ciliary-body 時間: 2025-3-24 07:33 作者: 壓倒性勝利 時間: 2025-3-24 14:45 作者: 易受刺激 時間: 2025-3-24 16:11
Textbook 2001te Uni- versity more than 25 years ago. It soon became evident. that many of the students who wanted to take the course (including engineers, computer scientists, and statis- ticians, as well as mathematicians) did not have the necessary prerequisites such as a working knowledge of Lp-spaces and som作者: 加入 時間: 2025-3-24 21:40 作者: PALL 時間: 2025-3-25 01:32 作者: Sigmoidoscopy 時間: 2025-3-25 04:15
Bounded Linear Functionals and Best Approximation from Hyperplanes and Half-Spaces,sely those that “attain their norm” (Theorem 6.12). We should mention that many of the results of this chapter—particularly those up to Theorem 6.12—can be substantially simplified or omitted entirely if the space . is assumed ., i.e., if . is a Hilbert space. Because many of the important spaces th作者: conformity 時間: 2025-3-25 07:48 作者: backdrop 時間: 2025-3-25 13:35 作者: Apraxia 時間: 2025-3-25 19:41
Best Approximation in Inner Product Spaces978-1-4684-9298-9Series ISSN 1613-5237 Series E-ISSN 2197-4152 作者: Admonish 時間: 2025-3-25 22:46 作者: 莎草 時間: 2025-3-26 04:03 作者: 不要嚴(yán)酷 時間: 2025-3-26 05:07 作者: 最高峰 時間: 2025-3-26 09:56
Existence and Uniqueness of Best Approximations,ce theorems of interest. In particular, the two most useful existence and uniqueness theorems can be deduced from it. They are: (1) Every finite-dimensional subspace is Chebyshev, and (2) every closed convex subset of a Hilbert space is Chebyshev.作者: heartburn 時間: 2025-3-26 12:58 作者: relieve 時間: 2025-3-26 16:58 作者: genuine 時間: 2025-3-26 21:20
Qiang Xu,Changjun Li,Ming Ronnier LuoWe will describe the general problem of best approximation in an inner product space. A uniqueness theorem for best approximations from convex sets is also provided. The five problems posed in Chapter 1 are all shown to be special cases of best approximation from a convex subset of an appropriate inner product space.作者: Observe 時間: 2025-3-27 03:53 作者: 憎惡 時間: 2025-3-27 07:13 作者: Antagonism 時間: 2025-3-27 09:52 作者: Fraudulent 時間: 2025-3-27 17:25
Constrained Interpolation from a Convex Set,In many problems that arise in applications, one is given certain function values or “data” along with some reliable evidence that the unknown function that generated the data has a certain shape. For example, the function may be nonnegative or nondecreasing or convex. The problem is to recover the unknown function from this information.作者: Respond 時間: 2025-3-27 18:47 作者: ENACT 時間: 2025-3-27 22:49
Lecture Notes in Electrical Engineering” approximation. While these problems seem to be quite different on the surface, we will later see that the first three (respectively the fourth and fifth) are special cases of the general problem of . (respectively .. In this latter formulation, the problem has a rather simple geometric interpretat作者: 自傳 時間: 2025-3-28 02:20
https://doi.org/10.1007/978-981-19-9024-3ce theorems of interest. In particular, the two most useful existence and uniqueness theorems can be deduced from it. They are: (1) Every finite-dimensional subspace is Chebyshev, and (2) every closed convex subset of a Hilbert space is Chebyshev.作者: cardiopulmonary 時間: 2025-3-28 08:57
https://doi.org/10.1007/978-981-19-9024-3deed, it will be the basis for . characterization theorem that we give. The notion of a dual cone plays an essential role in this characterization. In the particular case where the convex set is a subspace, we obtain the familiar orthogonality condition, which for finite-dimensional subspaces reduce作者: 整理 時間: 2025-3-28 12:09
Qiang Xu,Changjun Li,Ming Ronnier Luoand, if . is a subspace, even linear. There are a substantial number of useful properties that . possesses when . is a subspace or a convex cone. For example, every inner product space is the direct sum of any Chebyshev subspace and its orthogonal complement. More generally, a useful duality relatio作者: chronicle 時間: 2025-3-28 17:17
Nanlin Xu,Ming Ronnier Luo,Xinchao Qusubspaces, these functionals are the most important linear mappings that arise in our work. We saw in the last chapter that every element of the inner product space . naturally generates a bounded linear functional on . (see Theorem 5.18). Here we give a general representation theorem for . bounded 作者: 無效 時間: 2025-3-28 22:43
Hui Fan,Ming Ronnier Luo,Xinchao Qu given an explicit formula for the distance . in the last chapter (Theorem 6.25), and a strengthening of this distance formula in the particular case where the convex set . is either a convex cone or a subspace (Theorem 6.26). Now we will extract still further refinements, improvements, and applicat作者: subacute 時間: 2025-3-29 00:35 作者: TAIN 時間: 2025-3-29 06:07
https://doi.org/10.1007/978-3-319-45699-7terpolation (SAI), simultaneous approximation and norm-preservation (SAN), simultaneous interpolation and norm-preservation (SIN), and simultaneous approximation and interpolation with norm-preservation (SAIN).作者: arabesque 時間: 2025-3-29 07:32 作者: considerable 時間: 2025-3-29 11:31
978-1-4419-2890-0Springer-Verlag New York 2001作者: CT-angiography 時間: 2025-3-29 16:57 作者: 分離 時間: 2025-3-29 23:03
