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Saad Y. — Iterative methods for sparse linear systems
Saad Y. — Iterative methods for sparse linear systems



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Название: Iterative methods for sparse linear systems

Автор: Saad Y.

Аннотация:

Tremendous progress has been made in the scientific and engineering disciplines regarding the use of iterative methods for linear systems. This second edition gives an in-depth, up-to-date view of practical algorithms for solving large-scale linear systems of equations, including a wide range of the best methods available today.


Язык: en

Рубрика: Математика/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: 2

Год издания: 2003

Количество страниц: 547

Добавлена в каталог: 23.10.2010

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Reordering, for ILU      333
Reorthogonalization      10
Residual norm steepest descent      142
Residual projection methods      134
Residual smoothing      181 182
Restarted FOM      160
Restriction      421
Restriction operator      109 468
Reverse Cuthill — McKee ordering      see “RCM”
Richardson's iteration      114 250 412
Right versus left preconditioning      272
Right-hand side      37 103
Right-hand side, multiple      211
Rivest, R.L.      317
Rivlin, T.J.      201
Rose — Tarjan theorem      298
Roux, J.X.      493
Row projection methods      247 401
Row projection methods, parallel      401
Row reordering      78
Row sum      305
Ruge, A.      449
Ruhe, A.      209
Rutishauser, H.      404
Saddle-point problems      254
Sadok, H.      216 243
Saltz, J.      375
Sameh, A.      259
Saunders, M.A.      189
saxpy      137 324 360
SAXPY, parallel      360
SAXPY, sparse      324
Scatter and gather operations      362—363
Schoenauer, W.      216 243
Schultz, M.H.      319
Schur complement      456
Schur complement, and direct solution      456
Schur complement, approaches      477
Schur complement, for finite element partitionings      460
Schur complement, for model problems      463
Schur complement, for vertex partitionings      458
Schur complement, local      460
Schur complement, methods      477
Schur complement, properties      457
Schur form      16
Schur form, example      17
Schur form, nonuniqueness      18
Schur form, partial      17
Schur form, quasi      17
Schur form, real      17
Schwarz alternating procedure      455 465
Schwarz alternating procedure, additive      472
Schwarz alternating procedure, algorithm      465
Schwarz alternating procedure, multiplicative      465
Schwarz, H.A.      492
Search subspace      129
Section of an operator      153
Self-adjoint      6 473
Self-preconditioning      324
Self-preconditioning, convergence behavior      326
Semisimple      15
Separators      484
Set decomposition      108
Shared memory computers      356
Sherman, A.H.      319
Sidi, A.      244
Similarity transformation      14
Simon, H.D.      350 375 493
Simoncini, V.      216 243
Simple eigenvalue      14
Singular matrix      3
Singular values      9
Sites (in graph partitioning)      488
Skew — Hermitian, matrices      4 20 198
Skew — Hermitian, part      30
Skew-symmetric matrices      4
Skjellum, A.      359
Skyline solvers      84
Smith, B.      493
Smooth modes      407
Smoother      423
Smoothing operator      423
Smoothing property      435
Sonneveld, P.      229 243
SOR      105
SOR, convergence      119
SOR, for SPD matrices      119
SOR, iteration      103
SOR, multicolor sweep      392
Span of q-vectors      9
sparse      63
Sparse Gaussian elimination      75 93
Sparse matrices, adjacency graph      75
Sparse matrices, basic operations      92
Sparse matrices, direct methods      93
Sparse matrices, graph representation      75
Sparse matrices, matrix-by-vector operation      92
Sparse matrices, permutation and reordering      77
Sparse matrices, storage      89—92
Sparse matrix-by-vector product      92
Sparse skyline storage format      see “SSK”
Sparse triangular system solution      93
Sparse-sparse mode computations      323
Sparsity      73
SPARSKIT      94—97
SPD      see “Symmetric positive definite”
Spectral bisection      486
Spectral radius      3
Spectrum of a matrix      3
Split preconditioning      262
Splitting      105
Square matrices      2
SSK storage format      314
SSOR      105
Steepest descent      138
Stencil      49
Stereographic projection      485
Stewart, G.W.      43
Stewart, W.J.      449
Stiefel, E.L.      215 380 404
Stieltjes algorithm      187
Stiffness matrix      64 65
Stokes problem      256
Storage format, coordinate      89
Storage format, CSC      90
Storage format, CSR      90 291
Storage format, Ellpack — Itpack      91
Storage format, MSR      90
Storage format, SSK      314
Storage of sparse matrices      89—92
Strang, G.      72
Structural nonsingularity      336
Structured sparse matrix      73
Stueben, K.      449
Subdomain      397
subspace      9
Subspace, direct sum      9
Subspace, of approximants      129
Subspace, of constraints      129
Subspace, orthogonal      10
Subspace, sum      9
Successive overrelaxation      see “SOR”
Swartzrauber, P.N.      59
Sweet, R.      72
Symbolic factorization      93
Symmetric Gauss — Seidel      105
Symmetric matrices      4
Symmetric positive definite      30 119
Symmetric SOR      see “SSOR”
Symmetric squaring      342
Symmetry in preconditioned CG      262
Szyld, D.B.      281 350
Tang, W.P.      350
Taylor, D.R.      220 221
Teng, S.H.      484 485
Tensor product      411
Tensor sum      411
Test problems      94
TFQMR      234
TFQMR, algorithm      239
Topological sorting      370
Trace      3
Transpose-Free QMR      see “TFQMR”
Transversal      335
Triad operation      364
Triangular systems      369
Triangular systems, distributed      399
Triangular systems, level scheduling      370
Triangular systems, sparse      369
Tridiagonal matrices      5
Trottenberg, U.      449
Tuma.M.T.      331 337 350
Unassembled matrix      65
Underdetermined      246
Undirected graph      75
Unitary matrices      4
Unstructured sparse matrix      73
Upper triangular matrices      4
Upwind schemes      52
Uzawa's method      254 255
van der Vorst, H.A.      233 243 280 349 375
Varga, R.S.      43 121 126 128 350 405
Variable preconditioner      273
Vassilevski, P.      280
Vavasis, S.A.      484 485
Vector, computers      355
Vector, of unknowns      103
Vector, operations      360
Vector, orthogonality      10
Vector, processors      355
Vector, updates      137 360
Vector, updates, parallel      360
Vertex (in a graph)      75
Vinsome.R K.W.      216
Voevodin, V.V.      216
Wachspress, E.L.      128
Wagner, C      449
Walker, H.R      156 183 216 228 244
Walter, A.      244
Wang, X.      345 351
Wathens, A.J.      350
Watts, J.W      350
Wave-fronts      370
Weak formulation      61
Weakly diagonally dominant matrix      116
Weiss, R.      182 216 243
Wesseling, P.      243 449
Widlund, O.B.      278 477
Wigton, L.B.      350
Wilders, P.      493
Wilkinson, B.      375
Wilkinson, J.H.      216 220
Winget regularization      401
Wu, C.H.      101
Xu, J.      477 493
Ye, Q.      281
Yeremin, A.Y      350
Young, D.M.      121 123 126 128 196 405
Young, D.P.      350
Zarantonello's lemma      201
Zhou, L.      183 216 228 244
Zlatev.Z.      101 350
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