標(biāo)題: Titlebook: Computational Methods for General Sparse Matrices; Zahari Zlatev Book 1991 Springer Science+Business Media B.V. 1991 Mathematica.Matrix.al [打印本頁(yè)] 作者: 手套 時(shí)間: 2025-3-21 17:34
書(shū)目名稱Computational Methods for General Sparse Matrices影響因子(影響力)
書(shū)目名稱Computational Methods for General Sparse Matrices影響因子(影響力)學(xué)科排名
書(shū)目名稱Computational Methods for General Sparse Matrices網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱Computational Methods for General Sparse Matrices網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱Computational Methods for General Sparse Matrices被引頻次
書(shū)目名稱Computational Methods for General Sparse Matrices被引頻次學(xué)科排名
書(shū)目名稱Computational Methods for General Sparse Matrices年度引用
書(shū)目名稱Computational Methods for General Sparse Matrices年度引用學(xué)科排名
書(shū)目名稱Computational Methods for General Sparse Matrices讀者反饋
書(shū)目名稱Computational Methods for General Sparse Matrices讀者反饋學(xué)科排名
作者: 侵蝕 時(shí)間: 2025-3-21 23:52 作者: 黃瓜 時(shí)間: 2025-3-22 00:39
https://doi.org/10.1007/978-3-030-29977-4lar code used to illustrate the implementations is .. Hence the two main storage schemes described in . the input storage scheme and the dynamic storage scheme, are applied. However, similar ideas can be implemented if other codes and/or other storage schemes are used.作者: PTCA635 時(shí)間: 2025-3-22 07:30
https://doi.org/10.1057/9780230613188e discussed in the previous chapter. In the present chapter some pivotal strategies that can successfully be used with the second implementation will be described and compared. The same rule is used in the selection of pivotal columns in these pivotal strategies. The differences arise because the row interchanges are not the same.作者: BUCK 時(shí)間: 2025-3-22 08:50
Exploiting Sparsity,is called .. General sparse matrices occur in the numerical treatment of many engineering and scientific models. Both computing time and storage can be saved when sparsity is exploited. Moreover, many large problems can successfully be solved only when sparsity is exploited.作者: 背帶 時(shí)間: 2025-3-22 16:10 作者: 背帶 時(shí)間: 2025-3-22 18:32
Implementation of the Algorithms,lar code used to illustrate the implementations is .. Hence the two main storage schemes described in . the input storage scheme and the dynamic storage scheme, are applied. However, similar ideas can be implemented if other codes and/or other storage schemes are used.作者: Perceive 時(shí)間: 2025-3-22 21:56
Pivotal Strategies for Givens Plane Rotations,e discussed in the previous chapter. In the present chapter some pivotal strategies that can successfully be used with the second implementation will be described and compared. The same rule is used in the selection of pivotal columns in these pivotal strategies. The differences arise because the row interchanges are not the same.作者: HAIL 時(shí)間: 2025-3-23 04:08
Peter Busch-Jensen,Ernst Schraubehis chapter that codes for solving systems of linear algebraic equations can very easily be used to solve linear least squares problems by augmenting the coefficient matrix. . will be used, but this is done only to facilitate the exposition (the ideas could also be used in other codes).作者: 切掉 時(shí)間: 2025-3-23 08:58 作者: Hallmark 時(shí)間: 2025-3-23 10:50
https://doi.org/10.1007/978-3-030-29977-4ck of such a balance leads to catastrophic results, will be demonstrated in this chapter. Several pivotal strategies will be described and tested on many systems with sparse matrices. Some recommendations concerning the choice of a pivotal strategy for a sparse matrix code will be given.作者: 嚴(yán)厲譴責(zé) 時(shí)間: 2025-3-23 15:05
Pivotal Strategies for Gaussian Elimination,ck of such a balance leads to catastrophic results, will be demonstrated in this chapter. Several pivotal strategies will be described and tested on many systems with sparse matrices. Some recommendations concerning the choice of a pivotal strategy for a sparse matrix code will be given.作者: Peristalsis 時(shí)間: 2025-3-23 19:39 作者: conduct 時(shí)間: 2025-3-23 22:54 作者: BRINK 時(shí)間: 2025-3-24 02:56 作者: DAUNT 時(shí)間: 2025-3-24 07:07 作者: angiography 時(shí)間: 2025-3-24 10:40
Toward a Psychology of Possible SelvesThe main conclusion drawn in the previous chapter was: .. Two different implementations of sparse matrix techniques in connection with the Givens plane rotations will be described in this section. Both implementations are very attractive for certain classes of problems and/or for certain computer environments.作者: AXIS 時(shí)間: 2025-3-24 16:10 作者: 概觀 時(shí)間: 2025-3-24 19:35 作者: 玩忽職守 時(shí)間: 2025-3-25 00:41
Two Storage Schemes for Givens Plane Rotations,The main conclusion drawn in the previous chapter was: .. Two different implementations of sparse matrix techniques in connection with the Givens plane rotations will be described in this section. Both implementations are very attractive for certain classes of problems and/or for certain computer environments.作者: acetylcholine 時(shí)間: 2025-3-25 04:59 作者: 他很靈活 時(shí)間: 2025-3-25 11:09 作者: 獎(jiǎng)牌 時(shí)間: 2025-3-25 13:56 作者: catagen 時(shí)間: 2025-3-25 17:31
https://doi.org/10.1007/978-3-030-45590-3nor a special structure (such as bandedness). Assume that many of the elements a. ∈ A (i=1,2, ... ,m, j=1,2, ... ,n) are equal to zero. Then matrix A is called .. General sparse matrices occur in the numerical treatment of many engineering and scientific models. Both computing time and storage can b作者: Rodent 時(shí)間: 2025-3-25 21:55 作者: Mendacious 時(shí)間: 2025-3-26 01:04 作者: Soliloquy 時(shí)間: 2025-3-26 06:52 作者: 保守 時(shí)間: 2025-3-26 12:16 作者: Abbreviate 時(shí)間: 2025-3-26 15:18
Peter Busch-Jensen,Ernst Schraubeix technique is a very useful option in a package for solving such systems numerically. Such an option, the code . is described in this chapter. . is written for systems of ., but the same ideas can be applied to systems of non-linear ..作者: 整體 時(shí)間: 2025-3-26 20:11 作者: AXIOM 時(shí)間: 2025-3-27 00:53 作者: ALIAS 時(shí)間: 2025-3-27 05:02 作者: 可耕種 時(shí)間: 2025-3-27 06:01
https://doi.org/10.1057/9780230613188rge and sparse linear least squares problems. Two implementations of the Givens plane rotations for large and sparse linear least squares problems were discussed in the previous chapter. In the present chapter some pivotal strategies that can successfully be used with the second implementation will 作者: 煞費(fèi)苦心 時(shí)間: 2025-3-27 12:53 作者: Culpable 時(shí)間: 2025-3-27 17:15
https://doi.org/10.1007/978-1-349-73900-4mation to x = A.b = (A.A).A.b is to be calculated. In this chapter it will be shown that this problem can be transformed into an equivalent problem, which is a system of linear algebraic equations Cy=d whose coefficient matrix C is symmetric and positive definite. Moreover, C can be written as C = D作者: 石墨 時(shí)間: 2025-3-27 19:04
Sparse Matrix Technique for Ordinary Differential Equations,ix technique is a very useful option in a package for solving such systems numerically. Such an option, the code . is described in this chapter. . is written for systems of ., but the same ideas can be applied to systems of non-linear ..作者: flutter 時(shí)間: 2025-3-27 23:04
Orthogonalization Methods,umns (Q.Q=I, I being the identity matrix in R.), D ∈ .. is a diagonal matrix and R ∈ .. is an upper triangular matrix. Very often matrix D is the identity matrix and if this is so, then (12.1) is reduced to 作者: Aggregate 時(shí)間: 2025-3-28 03:25 作者: 燒瓶 時(shí)間: 2025-3-28 10:11
Overview: 978-90-481-4086-2978-94-017-1116-6作者: 用手捏 時(shí)間: 2025-3-28 11:43 作者: 燈絲 時(shí)間: 2025-3-28 15:11
https://doi.org/10.1057/9780230613188umns (Q.Q=I, I being the identity matrix in R.), D ∈ .. is a diagonal matrix and R ∈ .. is an upper triangular matrix. Very often matrix D is the identity matrix and if this is so, then (12.1) is reduced to 作者: gerrymander 時(shí)間: 2025-3-28 21:37
https://doi.org/10.1057/9780230613188 However, the classical manner of exploiting sparsity (see . is in fact used in the calculations because the drop-tolerance used is so small (T=10.) that practically no non-zero elements are removed during the decomposition process.作者: 可商量 時(shí)間: 2025-3-29 01:34 作者: myopia 時(shí)間: 2025-3-29 05:02
Preconditioned Conjugate Gradients for Givens Plane Rotations,trix Q ∈ .. with orthonormal columns (see .) and if the calculations are performed without rounding errors, then C=I and, thus, the CG algorithm converges in one iteration only. Even if the orthogonalization is carried out with rounding errors, the matrix C is normally close to the identity matrix I作者: insurgent 時(shí)間: 2025-3-29 08:33
https://doi.org/10.1007/978-3-319-26914-6ents) of the system by Gaussian elimination, .. This is so because the factorization process can be optimized quite well, while it is difficult to improve very much the performance of the back solver. The factorization time is by far the most expensive part when the . is used, while very often the s作者: 軟膏 時(shí)間: 2025-3-29 13:03
https://doi.org/10.1007/978-1-349-73900-4trix Q ∈ .. with orthonormal columns (see .) and if the calculations are performed without rounding errors, then C=I and, thus, the CG algorithm converges in one iteration only. Even if the orthogonalization is carried out with rounding errors, the matrix C is normally close to the identity matrix I作者: 腐敗 時(shí)間: 2025-3-29 19:03 作者: 流動(dòng)才波動(dòng) 時(shí)間: 2025-3-29 20:06
Pivotal Strategies for Gaussian Elimination,sed in the solution of linear algebraic equations with general sparse matrices, then the pivotal strategy plays a very important role. The pivotal strategy is a powerful tool that can efficiently be used during the efforts to preserve as well as possible the sparsity of the original matrix and, at t作者: TRAWL 時(shí)間: 2025-3-30 00:25
Use of Iterative Refinement in the GE Process, whose coefficient matrices are ., then the accuracy of the results will usually be greater than the accuracy obtained by the use of Gaussian elimination without iterative refinement (.). However, both more storage (about 100% because a copy of matrix A is needed) and more computing time (some extra作者: chassis 時(shí)間: 2025-3-30 05:30 作者: Scintigraphy 時(shí)間: 2025-3-30 09:43 作者: Horizon 時(shí)間: 2025-3-30 12:50
Sparse Matrix Technique for Ordinary Differential Equations,ix technique is a very useful option in a package for solving such systems numerically. Such an option, the code . is described in this chapter. . is written for systems of ., but the same ideas can be applied to systems of non-linear ..作者: PUT 時(shí)間: 2025-3-30 18:26 作者: SOBER 時(shí)間: 2025-3-30 22:40
Parallel Orthomin for General Sparse Matrices,positive definiteness, . A has no special structure, such as bandedness, . A is large and contains many zeros. It has been shown that the simple iterative refinement with some kind of dropping of “small” non-zero elements during the factorization (.) can successfully be used to improve the performan作者: Missile 時(shí)間: 2025-3-31 02:45
Orthogonalization Methods,umns (Q.Q=I, I being the identity matrix in R.), D ∈ .. is a diagonal matrix and R ∈ .. is an upper triangular matrix. Very often matrix D is the identity matrix and if this is so, then (12.1) is reduced to 作者: 愛(ài)哭 時(shí)間: 2025-3-31 07:35 作者: 開(kāi)花期女 時(shí)間: 2025-3-31 12:59
Iterative Refinement after the Plane Rotations, However, the classical manner of exploiting sparsity (see . is in fact used in the calculations because the drop-tolerance used is so small (T=10.) that practically no non-zero elements are removed during the decomposition process.作者: intention 時(shí)間: 2025-3-31 16:00 作者: Ferritin 時(shí)間: 2025-3-31 19:03
Book 2002ael. Structural analysis is a main part of any design problem, and the analysis often must be repeated many times during the design process. Much work has been done on design-oriented analysis of structures recently and many studies have been published. The purpose of the book is to collect together
