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Higham N.J. — Accuracy and Stability of Numerical Algorithms
Higham N.J. — Accuracy and Stability of Numerical Algorithms



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Название: Accuracy and Stability of Numerical Algorithms

Автор: Higham N.J.

Аннотация:

What is the most accurate way to sum floating point numbers? What are the advantages of IEEE arithmetic? How accurate is Gaussian elimination and what were the key breakthroughs in the development of error analysis for the method? The answers to these and many related questions are included here.

This book gives a thorough, up-to-date treatment of the behavior of numerical algorithms in finite precision arithmetic. It combines algorithmic derivations, perturbation theory, and rounding error analysis. Software practicalities are emphasized throughout, with particular reference to LAPACK and MATLAB. The best available error bounds, some of them new, are presented in a unified format with a minimum of jargon. Because of its central role in revealing problem sensitivity and providing error bounds, perturbation theory is treated in detail.

Historical perspective and insight are given, with particular reference to the fundamental work of Wilkinson and Turing, and the many quotations provide further information in an accessible format.

The book is unique in that algorithmic developments and motivations are given succinctly and implementation details minimized, so that attention can be concentrated on accuracy and stability results. Here, in one place and in a unified notation, is error analysis for most of the standard algorithms in matrix computations. Not since Wilkinson's Rounding Errors in Algebraic Processes (1963) and The Algebraic Eigenvalue Problem (1965) has any volume treated this subject in such depth. A number of topics are treated that are not usually covered in numerical analysis textbooks, including floating point summation, block LU factorization, condition number estimation, the Sylvester equation, powers of matrices, finite precision behavior of stationary iterative methods, Vandermonde systems, and fast matrix multiplication.

Although not designed specifically as a textbook, this volume is a suitable reference for an advanced course, and could be used by instructors at all levels as a supplementary text from which to draw examples, historical perspective, statements of results, and exercises (many of which have never before appeared in textbooks). The book is designed to be a comprehensive reference and its bibliography contains more than 1100 references from the research literature.

Audience

Specialists in numerical analysis as well as computational scientists and engineers concerned about the accuracy of their results will benefit from this book. Much of the book can be understood with only a basic grounding in numerical analysis and linear algebra.

About the Author

Nicholas J. Higham is a Professor of Applied Mathematics at the University of Manchester, England. He is the author of more than 40 publications and is a member of the editorial boards of the SIAM Journal on Matrix Analysis and Applications and the IMA Journal of Numerical Analysis. His book Handbook of Writing for the Mathematical Sciences was published by SIAM in 1993.


Язык: en

Рубрика: Математика/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: 2

Год издания: 2002

Количество страниц: 680

Добавлена в каталог: 19.06.2009

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Ng, Michael K.      457
Nickel, Karl      85 482 483
Nilson, E.N.      154
Nocedal, Jorge      226 468
Nonsymmetric positive definite matrix      208
Nonsymmetric positive definite matrix, LU factorization, stability of      208—209
Nordio, Marcelo      189
Norm      105—117
Norm $\left\| \ \cdot \ \right\|_{\alpha, \beta}$, explicit formulae for      116
Norm consistent      108
Norm, 2-norm, evaluation without overflow      499—500
Norm, absolute      107
Norm, dual      107
Norm, Hoelder inequality      106
Norm, matrix      107—112
Norm, matrix norm equivalence constants      109
Norm, matrix p-norm      112—114
Norm, matrix p-norm of magic square matrix      115
Norm, monotone      107
Norm, Probenius      107
Norm, subordinate matrix      108 109
Norm, unitarily invariant      108
Norm, vector      106—107
Norm, vector norm equivalence constants      109
Normal distribution      3
Normal equations      382 405
Normal equations error analysis      386—388
Notation, explanation of      2—3 67—69
Notay, Yvan      324
NPSOL      189
Numerical analysis, definition      5—6
Numerical radius      343
Numerical stability definition      7 29
Numerical stability for linear equation solvers      129—130
O'Cinneide, Colm Art      133
O'Leary, Dianne Prost      302
Oberaigner, W.      88
Oettli — Prager backward error theorem      122
Oettli, W.      122 132
Ofman, Yu.      447
Olesky, D.D.      190
Oliver, J.      103 428
Olkin, Ingram      524 525
Olshevsky, V.      428 429
Olver, F.W.J.      49 69 77 102 187
Omladic, Matjaz      210
Opfer, Gerhard      429
Ordinary differential equations accuracy of mesh point formation      92
Ordinary differential equations, backward error in      29
Ordinary differential equations, Euler's method with compensated summation      86
Ortega, James M.      376
Osborne, M.R.      413
Ostrowski, A.M.      344 543
Outer product, error analysis      64—65
Overflow      16 38
Overflow, avoiding      499—501
Overton, Michael L.      35
P-norm power method      289—291 301—302
Paige, Christopher C.      190 209 371 376 377 380 386 397 403 404 407 413 414 565
Pair wise elimination      180 189
Pairwise (fan-in) summation      80
Palmer, John      522
Palmer, Kenneth J.      29
Pan, Ching-Tsuan      183
Pan, Victor Y.      278 282 429 436 437 446
Papadimitriou, Pythagoras      377
Papadopoulos, Philip M.      318
Parallel prefix operation      103 152
Paranoia code      495
Parhami, Behrooz      56
Park, Haesun      376
Parlett, Beresford N.      xxviii xxx 24 30 55 76 79 184 215 226 353 375 376
Partial pivoting      158 162
Partial pivoting for skew-symmetric matrices      225
Partial pivoting for symmetric indefinite matrices      216—219
Partial pivoting growth factor      166—173
Partial pivoting growth factor, large growth in practical problems      167
Partial pivoting, early use of      188
Partial pivoting, threshold pivoting      193
Partitioned algorithm, definition      246
Partitioned LU factorization      246
Partitioned LU factorization, error analysis      249—250
Pascal matrix      518—521
Pascal matrix, Cholesky factor      519
Pascal matrix, eigenvalue reciprocity      519
Pascal matrix, inverse      520
Pascal matrix, total positivity      520
Pasternak, Mary E.      485
Patashnik, Oren      79 518
Paterson, Michael S.      102
Patrick, Merrell L.      227
Patriot missile software problem      503—504
Patterson, David A.      35 53
Paxson, Vern      57
Pei matrix      284 304
Pelz, Richard      502
Pena, J.M.      152 179 180 189 190
Pentium chip, division bug      55
Penzl, Thilo      317
Percival, Colin      457
Pereyra, Victor      423 423 425 429
Performance profile, for LAPACK norm estimator      294
Perturbation theory by calculus      132
Perturbation theory, linear systems      119—137
Perturbation theory, statistical      133 136
Perturbation theory, Sylvester equation      313—315
Peters, G.      103 188 275 281 282 404
Peterson, Brian      189
Philippe, Bernard      376
pi ($\pi$), high-precision calculation as computer test      489
Pichat, M.      88
Pierce, Daniel J.      299
Pinkus, Allan      186 188
Plemmons, Robert J.      133 152 180 190 299 332 404 413
Polar decomposition      377 380
Poljak, Svatopluk      128
Polman, Ben      257
Polynomials      93—104; see also “Horner's method”
Polynomials, divided differences      99—101
Polynomials, fast evaluation schemes      103—104
Polynomials, matrix, evaluation of      102
Polynomials, Newton form      99—101
Ponceleon, Dulce B.      227
Poole, George      188
Poromaa, Peter      302 315 318
PORT library, machine constants      497
Portability of software      496—499
Positive definite matrix      see “Nonsymmetric positive definite matrix” “Symmetric
Pothen, Alex      153
Powell, M.J.D.      210 362 375 395 404 472 474
Power method      22
Power method for matrix      1
Power method for matrix p-norm estimation      289—291 301—302
Power method, norm estimation      292—295
Power, Stephen      209
Powers of a matrix      339—352
Powers of a matrix in exact arithmetic      340—346
Powers of a matrix in finite precision arithmetic      346—350
Powers of a matrix, behaviour of stationary iteration      351
Powers of a matrix, departure from normality      344—345
Powers of a matrix, hump      342—343
Powers of a matrix, pseudospectrum      345—346 349—350
Powers of a matrix, role of spectral radius      340—342
Prager, W.      122 132
Precise      486
Precision effect of increasing      17—19
Precision versus accuracy      6 28
Preparata, F.P.      282
Press, William H.      476 487 505
Priest, Douglas M.      28 29 54 87—89 92 499 501 529
Program verification, applied to error analysis      485
Pryce, J.D.      69 241
Pseudo-inverse      382 402 405 408
Pseudospectral radius      345
Pseudospectrum      345—346 349—350
Pseudospectrum of companion matrix      523
Puglisi, Chiara      365
Pukelsheim, Friedrich      317
Puschmann, Heinrich      189
Pythagorean sum      500 507—509
QR factorization      355
QR factorization column pivoting      362 378
QR factorization iterative refinement for linear system      368—369
QR factorization perturbation theory      373—374
QR factorization rank-revealing      377
QR factorization row pivoting      362
QR factorization row sorting      362
QR factorization, generalized      397—398
QR factorization, Givens      365—366
QR factorization, Givens, cancellation of errors in      21—22
QR factorization, Givens, error analysis      366—368
QR factorization, Householder      355—357
QR factorization, Householder, error analysis      359—363
QR factorization, Householder, error analysis for application to LS problem      384—385
QR factorization, Householder, error analysis for partitioned (WY representation)      363—365
Quadratic equation, solving      10—11 29
Quadrature accuracy of grid formation      92
Quadrature error bound for evaluation of rule      78
Quasidefinite matrix      see “Symmetric quasidefinite matrix”
Quinlan, Gerald D.      87
Quinn, Thomas R.      87
Quintana, Enrique S.      282
Quintana, Gregorio      282
Rabinowitz, Philip      90
Rail, Louis B.      402 483 485
Raimi, Ralph A.      48
Ramos, George U.      456
Random matrices      515—518
Random matrices with given singular values      517—518
Random matrices, 2-norm of      516
Random matrices, condition number of      516
Random matrices, correlation matrices      525
Random matrices, expected number of real eigenvalues      516—517
Random matrices, orthogonal      517 524
Random matrices, spectral radius of      516
Random matrices, tend to be well conditioned      516
Randsvd matrix      517—518 524 525
Range reduction      51
Rath, Wolfgang      376
Ratz, H.C.      323
Razaz, M.      102
RCOND condition estimator (LAPACK, LINPACK, MATLAB)      302 477—478
Recursively partitioned LU factorization      248
Reese, M.S.      298
Reichel, Lothar      103 350 428—430 525
Reichelt, Mark W.      524
Reid, John K.      180 181 186 190 193 227 362 375 395 400 404
Reinsch, C.      xxix 281 57
Reiser, John F.      54
Relative error      3 4
Relative error counter, <k>      68
Relative error, componentwise      4
Relative precision      69
Relative residual      12
Ren, Huan      56
Renaut, R.E.      180
Research problems      92 104 193 212 229 242 304 319 352 406 430 449 469 487 525
Residual, relative      12
Rew, R.K.      287 297
Rheinboldt, Werner C.      467 467
Riccati equation, algebraic      316
Rice, John R.      29 376
Rigal — Gaches backward error theorem      120
Rigal, J.L.      120 132
Robertazzi, T.G.      89
Roberts, J.D.      317
Rohn, Jiff      116 128 135
Romani, Francesco      324
Rook pivoting      159—160 188
Rook pivoting for symmetric indefinite matrices      219—221
Rook pivoting, average number of comparisons      160 220
Rook pivoting, growth factor      170
Rose, Donald J.      257
Rosenthal, Peter      317
Ross, D.R.      88
Rounding      4 38
Rounding dealing with ties      38 54
Rounding error analysis model, standard      40
Rounding error analysis model, with underflow      56—57
Rounding error analysis model, without guard digit      44
Rounding error analysis notation      67—69
Rounding error analysis ordering of operations, effect of      70 141 142
Rounding error analysis purpose of      65 195
Rounding error analysis statistical approach      48—49
Rounding error analysis, automatic      471—487
Rounding error analysis, demystified      74—76
Rounding error analysis, graphs in      76
Rounding errors are not random      25—26 48
Rounding errors in subtraction      45
Rounding errors, accumulation of      14
Rounding errors, beneficial effects of      22—24
Rounding errors, cancellation of      19—22
Rounding errors, statistical assumptions on      48—49
Rounding modes in IEEE arithmetic      41
Rounding to even versus to odd      54
Rounding, monotonicity of      38
Rowan, Thomas Harvey      485 486
Rubin, Donald B.      381 402
Ruhe, Axel      376
Ruiz, Daniel      337
Rules of thumb condition for computed powers of matrix to converge to zero      350
Rules of thumb forward error related to backward error and condition number      9
Rules of thumb relative speed of floating point operations      56
Rules of thumb square root of constants in error bound      48
Rump, Siegfried M.      127—129 191 482 483
Runge — Kutta method      83 90
Running error analysis      66 486
Running error analysis for continued fraction      77
Running error analysis for Horner's method      95—96 103
Running error analysis for inner product      65—67
RussinofT, David M.      56
Rust, B.W.      132
Rutishauser, Heinz      512 518
Sadkane, Miloud      404
Sameh, Ahmed H.      150 151 180 485
Samelson, Klaus      53
Sample variance      see “Variance”
Sande, G.      456
Sanz-Serna, J.M.      29
Saunders, Michael A.      226 227 229 257 413
Sautter, Werner      186
Scalapack      580
Scaling a linear system before Gaussian elimination      177—179 190
Scaling to minimize the condition number      123 125—127 178
Scarborough, James B.      28 54
Schatzman, James C.      456
Schaumburg, Kjeld      302
Schelin, Charles W.      50
Scherer, R.      76
Schneider, Hans      112 115 352
Schonfelder, J.L.      102
Schreiber, Robert S.      153 168 180 245 250—253 256 257 278 365 375 571
Schryer, N.L.      496
Schulz iteration      183 278
Schulz, Giinther      183 278
Schur complement      203 209 215 246 252
Schur complement, perturbation bounds for symmetric positive semidefinite matrix      203—208
Schwartz, S.C.      89
Schwetlick, Hubert      77 393 404 410 414
Searle, Shayle R.      317 487
1 2 3 4 5 6 7
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