13
References [1] ABDULLE, A., AND WANNER, G. 200 years of least squares method. Elemente der Mathematik (2002). [2] ABRAMOWITZ, M., AND STEGUN, 1. A. Pocketbook of Mathematical Functions. Verlag Harri Deutsch, Thun, Frankfurt/Main, 1984. [3] AIGNER, M. Diskrete Mathematik, 4. ed. Vieweg, Braunschweig, Wiesbaden, 200l. [4] ANDERSON, E., BAI, Z., BISCHOF, C., DEMMEL, J., DONGARRA, J., DUCROZ, J., GREENBAUM, A., HAMMARLING, S., McKENNEY, A., OSTRU- CHOV, S., AND SORENSEN, D. LAPACK Users' Guide. SIAM, Philadelphia, 1999. [5] ARNOLDI, W. E. The principle of minimized iterations in the solution of the matrix eigenvalue problem. Quart. Appl. Math. 9 (1951), 17-29. [6] BABUSKA, 1., AND RHEINBOLDT, W. C. Error estimates for adaptive finite element computations. SIAM J. Numer. Anal. 15 (1978), 736-754. [7] BJ0RCK, A. Iterative refinement of linear least squares solutions I. BIT 7 (1967), 257-278. [8] BOCK, H. G. Randwertproblemmethoden zur Parameteridentijizierung in Systemen nichtlinearer Differentialgleichungen. PhD thesis, Universitiit zu Bonn, 1985. [9] BORNEMANN, F. A. An Adaptive Multilevel Approach to Parabolic Equations in two Dimensions. PhD thesis, Freie Universitiit Berlin, 1991. [10] BRENT, R. P. Algorithms for Minimization Without Derivatives. Prentice Hall, Englewood Cliffs, N.J., 1973. [11] BULIRSCH, R. Bemerkungen zur Romberg-Integration. Numer. Math. 6 (1964),6-16.

References - Springer978-0-387-21584-6/1.pdf · ... W. E. The principle of minimized iterations in the solution of the matrix ... AND MEYER, W. W ... C. D. Matrix Analysis and Applied

Embed Size (px)

Citation preview

References

[1] ABDULLE, A., AND WANNER, G. 200 years of least squares method. Elemente der Mathematik (2002).

[2] ABRAMOWITZ, M., AND STEGUN, 1. A. Pocketbook of Mathematical Functions. Verlag Harri Deutsch, Thun, Frankfurt/Main, 1984.

[3] AIGNER, M. Diskrete Mathematik, 4. ed. Vieweg, Braunschweig, Wiesbaden, 200l.

[4] ANDERSON, E., BAI, Z., BISCHOF, C., DEMMEL, J., DONGARRA, J., DUCROZ, J., GREENBAUM, A., HAMMARLING, S., McKENNEY, A., OSTRU­CHOV, S., AND SORENSEN, D. LAPACK Users' Guide. SIAM, Philadelphia, 1999.

[5] ARNOLDI, W. E. The principle of minimized iterations in the solution of the matrix eigenvalue problem. Quart. Appl. Math. 9 (1951), 17-29.

[6] BABUSKA, 1., AND RHEINBOLDT, W. C. Error estimates for adaptive finite element computations. SIAM J. Numer. Anal. 15 (1978), 736-754.

[7] BJ0RCK, A. Iterative refinement of linear least squares solutions I. BIT 7 (1967), 257-278.

[8] BOCK, H. G. Randwertproblemmethoden zur Parameteridentijizierung in Systemen nichtlinearer Differentialgleichungen. PhD thesis, Universitiit zu Bonn, 1985.

[9] BORNEMANN, F. A. An Adaptive Multilevel Approach to Parabolic Equations in two Dimensions. PhD thesis, Freie Universitiit Berlin, 1991.

[10] BRENT, R. P. Algorithms for Minimization Without Derivatives. Prentice Hall, Englewood Cliffs, N.J., 1973.

[11] BULIRSCH, R. Bemerkungen zur Romberg-Integration. Numer. Math. 6 (1964),6-16.

326 References

[12] BUSINGER, P., AND GOLUB, G. H. Linear least squares solutions by Householder transformations. Numer. Math. 'l (1965), 269-276.

[13] CULLUM, J., AND WILLOUGHBY, R. Lanczos Algorithms for Large Symmet­ric Eigenvalue Computations, Vol I, II. Birkhiiuser, Boston, 1985.

[14] DE BOOR, C. An algorithm for numerical quadrature. In Mathematical Software, J. Rice, Ed. Academic Press, London, 1971.

[15] DE BOOR, C. A Practical Guide to Splines, reprint ed. Springer-Verlag, Berlin, Heidelberg, New York, 1994.

[16] DEUFLHARD, P. On algorithms for the summation of certain special functions. Computing 17 (1976), 37-48.

[17] DEUFLHARD, P. A summation technique for minimal solutions of linear homogeneous difference equations. Computing 18 (1977), 1-13.

[18] DEUFLHARD, P. A stepsize control for continuation methods and its special application to multiple shooting techniques. Numer. Math. 33 (1979), 115-146.

[19] DEUFLHARD, P. Order and stepsize control in extrapolation methods. Numer. Math. 41 (1983), 399-422.

[20] DEUFLHARD, P. Newton Methods for Nonlinear Problems. Affine Invariance and Adaptive Algorithms. Springer International, 2002.

[21] DEUFLHARD, P., AND BAUER, H. J. A note on Romberg quadrature. Preprint 169, Universitiit Heidelberg, 1982.

[22] DEUFLHARD, P., AND BORNEMANN, F. Scientific Computing with Ordinary Differential Equations. Springer, New York, 2002.

[23] DEUFLHARD, P., FIEDLER, B., AND KUNKEL, P. Efficient numerical pathfollowing beyond critical points. SIAM J. Numer. Anal. 18 (1987), 949-987.

[24] DEUFLHARD, P., HUISINGA, W., FISCHER, A., AND SCHUTTE, C. Identifi­cation of almost invariant aggregates in reversible nearly uncoupled Markov chains. Lin. Alg. Appl. 315 (2000), 39-59.

[25] DEUFLHARD, P., LEINEN, P., AND YSERENTANT, H. Concept of an adap­tive hierarchical finite element code. Impact of Computing in Science and Engineering 1, 3 (1989), 3-35.

[26] DEUFLHARD, P., AND POTRA, F. A. A refined Gauss-Newton-Mysovskii theorem. ZIB Report SC 91-4, ZIB, Berlin, 1991.

[27] DEUFLHARD, P., AND POTRA, F. A. Asymptotic mesh independence for Newton-Galerkin methods via a refined Mysovskii theorem. SIAM J. Numer. Anal. 29,5 (1992), 1395-1412.

[28] DEUFLHARD, P., AND SAUTTER, W. On rank-deficient pseudoinverses. Lin. Alg. Appl. 29 (1980),91-111.

[29] ERICSSON, T., AND RUHE, A. The spectral transformation Lanczos method for the numerical solution of large sparse generalized symmetric eigenvalue problems. Math. Compo 35 (1980), 1251-1268.

[30] FARIN, G. Curves and Surfaces for Computer Aided Geometric Design: A Practical Guide. Academic Press, New York, 1988.

References 327

[31J FLETCHER, R. Conjugate gradient methods. In Pmc. Dundee Biennial Conference on Numerical Analysis. Springer Verlag, New York, 1975.

[32J FORSYTHE, G. E., AND MOLER, C. Computer Solution of Linear Algebra Systems. Prentice Hall, Englewood Cliffs, N.J., 1967.

[33J FRANCIS, J. G. F. The QR-transformation. A unitary analogue to the LR­transformation - Part 1 and 2. Compo J. 4 (1961/62),265-271 and 332-344.

[34J GATERMANN, K., AND HOHMANN, A. Symbolic exploitation of symmetry in numerical pathfollowing. Impact Compo Sci. Eng. 3,4 (1991), 330-365.

[35J GAUSS, C. F. Theoria Motus Corporum Coelestium. Vol. 7. Perthes et Besser, Hamburgi, 1809.

[36J GAUTSCHI, W. Computational aspects of three-term recurrence relations. SIAM Rev. 9 (1967), 24-82.

[37J GENTLEMAN, W. M. Least squares computations by Givens transformations without square roots. J. Inst. Math. Appl. 12 (1973), 189-197.

[38J GEORG, K. On tracing an implicitly defined curve by quasi-Newton steps and calculating bifurcation by local perturbations. SIAM J. Sci. Stat. Comput. 2, 1 (1981), 35-50.

[39J GEORGE, A., AND LIU, J. W. Computer Solution of Large Sparse Positive Definite Systems. Prentice Hall, Englewood Cliffs, N.J., 1981.

[40J GOERTZEL, G. An algorithm for the evaluation of finite trigonometric series. Amer. Math. Monthly 65 (1958), 34-35.

[41J GOLUB, G. H., AND VAN LOAN, C. F. Matrix Computations, second ed. The Johns Hopkins University Press, Baltimore, MD, 1989.

[42J GOLUB, G. H., AND WELSCH, J. H. Calculation of Gauss quadrature rules. Math. Compo 23 (1969), 221-230.

[43J GRADSHTEYN, 1. S., AND RYZHlK, 1. W. Table of Integral Series and Products, sixth ed. Academic Press, New York, San Francisco, London, 2000.

[44J GRIEWANK, A., AND CORLISS, G. F. Automatic Differentiation of Al­gorithms: Theory, Implementation, and Application. SIAM Publications, Philadelphia, PA, 1991.

[45J HACKBUSCH, W. Multi-Grid Methods and Applications. Springer Verlag, Berlin, Heidelberg, New York, Tokyo, 1985.

[46J HAGEMAN, L. A., AND YOUNG, D. M. Applied Iterative Methods. Academic Press, Orlando, San Diego, New York, 1981.

[47J HAIRER, E., N0RSETT, S. P., AND WANNER, G. Solving Ordinary Differ­ential Equations I, Nonstiff Problems. Springer Verlag, Berlin, Heidelberg, New York, Tokyo, 1987.

[48J HALL, C. A., AND MEYER, W. W. Optimal error bounds for cubic spline interpolation. J. Appmx. Theory 16 (1976), 105-122.

[49J HAMMARLING, S. A note on modifications to the Givens plane rotations. J. [nst. Math. Appl. 13 (1974), 215-218.

[50J HESTENES, M. R., AND STIEFEL, E. Methods of conjugate gradients for solving linear systems. J. Res. Nat. Bur. Stand 49 (1952), 409-436.

328 References

[51J HIGHAM, N. J. How accurate is Gaussian elimination? In Numerical Analy­sis, Pmc. 13th Biennial Conf., Dundee / UK 1989. Pitman Res. Notes Math. Ser. 228, 1990, pp. 137-154.

[52J HOUSEHOLDER, A. S. The Theory of Matrices in Numerical Analysis. Blaisdell, New York, 1964.

[53J IpSEN, I. C. F. A history of inverse iteration. In Helmut Wielandt, Mathe­matische Werke, Mathematical Works, B. Huppert and H. Schneider, Eds., vol. II: Matrix Theory and Analysis. Walter de Gruyter, New York, 1996, pp.464-72.

[54J KATO, T. Perturbation Theory for Linear Operators, reprint ed. Springer Verlag, Berlin, Heidelberg, New York, Tokyo, 1995.

[55J KNOPP, K. Theorie und Anwendung der unendlichen Reihen. Springer Verlag, Berlin, Heidelberg, New York, (5. Aufiage) 1964.

[56J KUBLANOVSKAYA, V. N. On some algorithms for the solution of the complete eigenvalue problem. USSR Compo Math. Phys. 3 (1961),637-657.

[57J LANCZOS, C. An iteration method for the solution of the eigenvalue prob­lem of linear differential and integral operators. J. Res. Nat. Bur. Stand 45 (1950), 255-282.

[58J MANTEUFFEL, T. A. The Tchebychev iteration for nonsymmetric linear systems. Numer. Math. 28 (1977), 307-327.

[59J MEIJERINK, J., AND VAN DER VORST, H. An iterative solution method for linear systems of which the coefficient matrix is a symmetric M-matrix. Math. Compo 31 (1977), 148-162.

[60J MEIXNER, J. R., AND SCHAFFKE, W. Mathieusche Funktionen und Sphiiroidfunktionen. Springer Verlag, Berlin, Gi:ittingen, Heidelberg, 1954.

[61J MEYER, C. D. Matrix Analysis and Applied Linear Algebra. SIAM Publications, Philadelphia, PA, 2000.

[62J MILLER, J. C. P. Bessel Functions, Part II (Math. Tables X). Cambridge University Press, Cambridge, UK, 1952.

[63J NASHED, M. Z. Generalized Inverses and Applications. Academic Press, New York, 1976.

[64J NIKIFOROV, A. F., AND UVAROV, V. B. Special Functions of Mathematical Physics. Birkhiiuser, Basel, Boston, 1988.

[65J PERRON, O. tiber Matrizen. Math. Annalen 64 (1907),248-263.

[66J POINCARE, H. Les Methodes Nouvelles de la Mecanique Celeste. Gauthier­Villars, Paris, 1892.

[67J POPPE, C., PELLICIARI, C., AND BACHMANN, K. Computer analysis of Feulgen hydrolysis kinetics. Histochemistry 60 (1979), 53-60.

[68J PRAGER, W., AND OETTLI, W. Compatibility of approximate solutions of linear equations with given error bounds for coefficients and right hand sides. Numer. Math. 6 (1964), 405-409.

[69J PRIGOGINE, I., AND LEFEVER, R. Symmetry breaking instabilities in dissipative systems II. J. Chem. Phys. 48 (1968), 1695-170l.

[70J REINSCH, C. A note on trigonometric interpolation. Manuscript, 1967.

References 329

[71] RIGAL, J. L., AND GACHES, J. On the compatibility of a given solution with the data of a linear system. J. Assoc. Comput. Mach. 14 (1967), 543-548.

[72] ROMBERG, W. Vereinfachte Numerische Integration. Det Kongelige Norske Videnskabers Selskabs Forhandlinger Bind 28, 7 (1955).

[73] SAUER, R., AND SZABO, 1. Mathematische Hilfsmittel des Ingenieurs. Springer Verlag, Berlin, Heidelberg, New York, 1968.

[74] SAUTTER, W. Fehlerfortpfianzung und Rundungsfehler bei der verallge­meinerten Inversion von Matrizen. PhD thesis, TU Miinchen, Fakultiit fiir Allgemeine Wissenschaften, 1971.

[75] SHANNON, C. E. The Mathematical Theory of Communication. The University of Illinois Press, Urbana, Chicago, London, 1949.

[76] SKEEL, R. D. Scaling for numerical stability in Gaussian elimination. J. ACM 26, 3 (1979), 494-526.

[77] SKEEL, R. D. Iterative refinement implies numerical stability for Gaussian elimination. Math. Compo 35, 151 (1980), 817-832.

[78] SONNEVELD, P. A fast Lanczos-type solver for nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 10 (1989), 36-52.

[79] STEWART, G. W. Introduction to Matrix Computations. Academic Press, New York, San Francisco, London, 1973.

[80] STEWART, G. W. On the structure of nearly uncoupled Markov chains. In Mathematical Computer Performance and Reliability, G. Iazeolla, P. J. Courtois, and A. Hordijk, Eds. Elsevier, New York, 1984.

[81] STOER, J. Solution of large systems of linear equations by conjugate gra­dient type methods. In Mathematical Programming, the State of the Art, A. Bachem, M. Grotschel, and B. Korte, Eds. Springer Verlag, Berlin, Heidelberg, New York, 1983.

[82] SZEGO, G. Orthogonal Polynomials, fourth ed. AMS, Providence, RI, 1975.

[83] TRAUB, J., AND WOZNIAKOWSKI, H. General Theory of Optimal Algorithms. Academic Press, Orlando, San Diego, San Francisco, 1980.

[84] TREFETHEN, L. N., AND SCHREIBER, R. S. Average-case stability of gaussian elimination. SIAM J. Matrix Anal. Appl. 11,3 (1990), 335-360.

[85] TUKEY, J. W., AND COOLEY, J. W. An algorithm for the machine calculation of complex Fourier series. Math. Comp 19 (1965), 197-30l.

[86] VARGA, J. Matrix Iterative Analysis. Prentice Hall, Englewood Cliffs, N.J., 1962.

[87] WILKINSON, J. H. Rounding Errors in Algebraic Processes. Her Majesty's Stationary Office, London, 1963.

[88] WILKINSON, J. H. The Algebraic Eigenvalue Problem. Oxford University Press, Oxford, UK, 1965.

[89] WILKINSON, J. H., AND REINSCH, C. Handbook for Automatic Computation, Volume II, Linear Algebra. Springer Verlag, New York, Heidelberg, Berlin, 1971.

[90] WITTUM, G. Mehrgitterverfahren. Spektrum der Wissenschajt (April 1990), 78-90.

330 References

[91] WULKOW, M. Numerical treatment of countable systems of ordinary differential equations. ZIB Report TR 90-8, ZIB, Berlin, 1990.

[92] Xu, J. Theory of Multilevel Methods. PhD thesis, Penn State University, 1989.

[93] YSERENTANT, H. On the multi-level splitting of finite element spaces. Numer. Math. 49 (1986), 379-4l2.

Software 331

Software

For most of the algorithms described in this book there exists rather so­phisticated software, which is public domain. Of central importance is the netlib, a library of mathematical software, data, documents, etc. Its address IS

http://www.netlib.org/

Linear algebra (LAPACK):

http://www.netlib.org/lapack

Especially linear eigenvalue problems (EISPACK):

http://www.netlib.org/eispack

Please study the therein given hints carefully (e.g., README, etc.) to make sure that you download all necessary material. Sometimes a bit of additional browsing in the neighborhood is needed.

The commercial program package MATLAB also offers a variety of methods associated with topics of this book.

In addition, the book presents a series of algorithms as informal algo­rithms which can be easily programmed from this description-such as the fast summation of spherical harmonics.

Numerous further programs (not only by the authors) can be downloaded from the electronic library Elib by ZIB, either via the ftp-oriented address

http://elib.zib.de/pub/elib/codelib/

or via the web-oriented address

http://www.zib.de/SciSoft/CodeLib/

All of the there available programs are free as long as they are exclusively used for research or teaching purposes.

Index

A-orthogonal, 250 Abel's theorem, 126 Aigner, M., 306 Aitken's L~.2-method, 114 Aitken-Neville algorithm, 184 algorithm

invariance, 12 reliability, 2 speed, 2

almost singular, 45, 73 Arnoldi method, 254 Arrhenius law, 79 asymptotic expansion, 292 automatic differentiation, 92

B-spline basis property, 224 recurrence relation, 221

Bezier curve, 208 points, 208

Babuska, 1., 315 backward substitution, 4 Bernoulli numbers, 288 Bessel

functions, 159, 177 maze, 159

bi-cg-method, 255 bifurcation point, 100 Bjorck, A., 66, 78 Bock, H. G., 96 Bornemann, F. A., 261 Brent, R. P., 85 Brusselator, 112 Bulirsch sequence, 297 Bulirsch, R., 293 Businger, P., 72

cancellation, 27 cascadic principle, 267 Casorati determinant, 157, 177 cg-method, 252

preconditioned, 257 termination criterion, 252, 260

Chebyshev abscissas, 195 approximation problem, 60 iteration, 247 nodes, 184, 196 polynomials, 193, 248

min-max property, 193, 246, 253 Cholesky decomposition

rational, 15 Christoffel-Darboux formula, 285

334 Index

complexity of problems, 2

condition intersection point, 24

condition number absolute, 26 componentwise, 32 of addition, 27 of multiplication, 32 of scalar product, 33 relative, 26 Skeel's, 33

conjugate gradients, 252 continuation method, 92

classical, 102 order, 104 tangent, 103, 108

convergence linear, 85 model, 309 monitor, 307 quadratic, 85 super linear, 85

Cooley, W., 202 cost

QR-factorization, 69, 72 Cholesky decomposition, 16 Gaussian elimination, 7 QR method

for singular values, 137 QR-algorithm, 132

Cramer's rule, 1 Cullum, J., 266 cylinder functions, 159

de Boor algorithm, 235 de Boor, C., 204, 309 de Casteljau algorithm, 213 detailed balance, 143 Deuflhard, P., 73, 90, 261, 308

eigenvalue derivative, 120 Perron, 140

elementary operation, 23 Ericsson, T., 266 error

absolute, 25 analysis

backward, 36 forward, 35

equidistribution, 316 linearised theory, 26 relative, 25

extrapolation algorithm, 295 local, 316 methods, 291, 295

sub diagonal error criterion, 304 tableau, 292

Farin, G., 204 FFT,203 fixed-point

Banach theorem, 84 equation, 82 iteration, 82, 239 method

symmetrizable, 242 Fletcher, R., 255 floating point number, 22 forward substitution, 4 Fourier

series, 152, 200 transform, 197

fast, 201 Francis, J. G. F., 127 Frobenius, F. G., 140

Gaches, J., 50 Gauss

Jordan decomposition, 3 Newton method, 109 Seidel method:, 240

Gauss, C. F., 4, 57 Gautschi, W., 164 generalized inverse, 76 Gentleman, W. M., 70 Givens

fast, 70 rational, 70 rotations, 68

Givens, W., 68 Goertzel algorithm, 171 Goertzel, G., 171 Golub, G. H., 47, 72, 119 graph, 140

irreducible, 140

strongly connected, 140 greedy algorithm, 306 Green's function

discrete, 157, 177 Griewank, A., 92

Hackbusch, W., 244 Hagemann, L. A., 244 Hall, C. A., 230 Hammarling, S., 70 Hermite interpolation

cubic, 186 Hestenes, M. R., 252 Higham, N. J., 46 homotopy, 111

method,l11 Horner algorithm, 169

generalized, 170 Householder

reflections, 70 Householder, A. S., 70

incidence matrix, 141 information theory

Shannon, 308 initial value problem, 270 interpolation

Hermite, 185 nodes, 179

iterative refinement for linear equations, 13 for linear least-squares problems,

66,78

Jacobi method, 240

Kato, T., 122 Krylov spaces, 250 Kublanovskaja, V. N., 127

Lagrange polynomials, 181 representation, 182

Lagrange, J. L., 4 Lanczos method

spectral, 266 Lanczos, C., 262 Landau symbol, 26 LAPACK,13

Index 335

Lebesgue constant, 183 Leibniz formula, 191 Leinen, P., 261 Levenberg-Marquardt method, 98,

117, 149

Manteuffel, T. A., 249 Markov

chain, 137 nearly uncoupled, 147, 150 reversible, 144 uncoupled, 145

process, 137 Markov, A. A., 137 Marsden identity, 223 matrix

bidiagonal, 134 determinant, 1, 12, 30 Hessenberg, 132, 254 incidence, 141 irreducible, 140 norms, 53 numerical range, 17 permutation, 9 primitive, 142 Spd-, 14 stochastic, 137 triangular, 3 Vandermonde, 181

maximum likelihood method, 59 measurement tolerance, 59 Meixner, J., 162 Meyer, C. D., 119 Meyer, W. W., 230 Miller algorithm, 167 Miller, J. C. P., 166, 168 monotonicity test

natural, 90, 106 standard, 90

multigrid methods, 244, 313, 320

Nashed, M. Z., 76 needle impulse, 298, 309, 319 Neumann

functions, 159, 177 series, 29

Neville scheme, 185 Newton

correction, 88

336 Index

simplified correction, 91 Newton method

affine invariance, 88, 90 complex, 115 for square root, 86

nodes Gauss-Christoffel, 282 of a quadrature formula, 273

nonlinear least-squares problem almost compatible, 96 compatible, 93

norm £1_,271 energy, 249 Frobenius, 53 matrix, 53 spectral, 53 vector, 53

normal distribution, 59 numerical rank, 73 numerically singular, 45

Oettli, W., 50, 55 Ohm's law, 58

pcg-method, 257, 267 Penrose axioms, 76 Perron cluster, 147

analysis, 143 Perron, 0., 138 pivot

element, 7 row, 5

pivoting column, 8 conditional, 238 partial, 8 total, 9

polynomials Bernstein, 205 Chebyshev, 154, 176, 193, 248, 285 Hermite, 186, 285 Laguerre, 285 Legendre, 164, 176, 285 orthogonal, 153, 279, 285 trigonometric, 197

power method direct, 124 inverse, 125

Prager, W., 50, 55 preconditioning

diagonal, 260 incomplete Cholesky, 260

pseudo-inverse, 75, 93, 109 QR-factorization, 76 singular value decomposition, 133

QR decomposition column permutation, 72

QR-algorithm shift strategy, 131

quadratic equation, 28, 81 quadrature

condition of problem, 271 error, 283

estimator, 301 formula, 273

Gauss-Christoffel, 282 Newton-Cotes, 275

Gauss-Chebyshev, 285 Gauss-Christoffel, 285 Gauss-Hermite, 285 Gauss-Laguerre, 285 Gauss-Legendre, 285 numerical, 270 parameter-dependent, 312

rank decision, 73 determination, 96

Rayleigh quotient, 262 generalized, 265

refinement global, 317 local, 317

Reinsch, C., 41, 132, 171 residual, 49 Rheinboldt, W. C., 315 Richardson method, 240

relaxed, 243 Rigal, J. L., 50 Ritz-Galerkin approximation, 249 Romberg quadrature

adaptive algorithm, 306 Romberg sequence, 296 Ruhe, A., 266 Rutishauser, H., 127

Sautter, W., 47, 73 scaling, 12

column, 12 row, 12

Schiiffke, W., 162 Schreiber, R. S., 49 Schur normal form, 132 Schur, I., 20 Shannon, C. E., 308 shift strategy, 130 Skeel, R. D., 14, 33, 51, 56 Sonneveld, P., 255 sparse solvers, 238, 266 sparsing, 92 special functions, 151 spectral equivalence, 259 spherical harmonics

algorithm, 163, 166 fast summation, 171

splines complete, 232 minimization property, 229 natural, 232

stability indicator, 37, 42 statistical model

inadequate, 96 steepest descent method, 255 step size, 103

basic, 295, 299 internal, 295

step-size control, 300

Stewart, G. W., 147 Stiefel, E., 252 stochastic process, 137 Stoer, J., 255 Sturm sequence, 178 subcondition, 73 substitution

backward, 4 forward, 4

Taylor interpolation, 186 three-term recurrence relation

adjoint, 170 condition, 161 dominant solution, 162 homogeneous, 156 inhomogeneous, 156, 158

Index 337

minimal solution, 162 symmetric, 156 trigonometric, 40, 162, 170

Traub, J., 2 Trefethen, L. N., 49 Tukey, J. W., 202 turning point, 100

van Loan, C., 47, 119 van Veldhuizen, R., 321 von Mises, R., 124

weight function, 279 weights

Gauss-Christoffel, 282, 285 Newton-Cotes, 275 of a quadrature formula, 273

Wielandt, H., 125, 143 Wilkinson

pathological example, 48, 56 Wilkinson, J. H., 36, 46, 47, 123, 129,

131, 132 Willoughby, R., 266 Wittum, G., 244 work per unit step, 306 Wozniakowski, H., 2 Wronski determinant, 158

Xu, J., 261

Young, D. M., 244 Yserentant, H., 261

Texts in Applied Mathematics

(continued from page ii)

3l. Bremaud: Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues. 32. Durran: Numerical Methods for Wave Equations in Geophysical Fluid

33.

34. 3 ~ ::J.

Dynamics. Thomas: Numerical Partial Differential Equations: Conservation Laws and

Elliptic Equations. Chicone: Ordinary Differential Equations with Applications.

Kevorkian: Partial Differential Equations: Analytical Solution Techniques, 2nd ed.

36. Dllllerlld/Paganini: A Course in Robust Control Theory: A Convex Approach. 37. Quarteroni/Sacco/Saleri: Numerical Mathematics. 38. Gallier: Geometric Methods and Applications: For Computer Science and

Engineering. 39. Atkinson/Han: Theoretical Numerical Analysis: A Functional Analysis

Framework. 40. Braller/Castill(}-Chimez: Mathematical Models in Population Biology and

Epidemiology. 41. Davies: Integral Transforms and Their Applications, 3rd ed. 42. Deuflhard/Bornemann: Scientific Computing with Ordinary Differential

Equations. 43. Deuflhard/Hohmann: Numerical Analysis in Modern Scientific Computing: An

Introduction, 2nd ed.