Numerical Analysis 2000 by Elsevier Publishing Company

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Numerical Analysis 2000 : Quadrature and Orthogonal Polynomials
By L. Reichel, W. Gautschi, F. Marcellan



  • Publisher: Elsevier Publishing Company
  • Number Of Pages: 384
  • Publication Date: 2001-04-01
  • ISBN-10 / ASIN: 0444506152
  • ISBN-13 / EAN: 9780444506153
  • Binding: Paperback


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Orthogonal polynomials play a prominent role in pure, applied, and computational mathematics, as well as in the applied sciences. It is the aim of the present volume in the series "Numerical Analysis in the 20th Century" to review, and sometimes extend, some of the many known results and properties of orthogonal polynomials and related quadrature rules. In addition, this volume discusses techniques available for the analysis of orthogonal polynomials and associated quadrature rules. Indeed, the design and computation of numerical integration methods is an important area in numerical analysis, and orthogonal polynomials play a fundamental role in the analysis of many integration methods. The 20th century has witnessed a rapid development of orthogonal polynomials and related quadrature rules, and we therefore c​


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Numerical Analysis 2000 : Partial Differential Equations (Numerical Analysis 2000, V. 7)
By: Keith Jones, D. Sloan (Editor) , E Suli, S. Vandewaite

ISBN: 0444506160
Publisher: Elsevier - 2001-07-01
Paperback | 480 Pages | List Price: $81.95 (USD) | Sales Rank: 3595430

Over the second half of the 20th century the subject area loosely referred to as numerical analysis of partial differential equations (PDEs) has undergone unprecedented development. At its practical end, the vigorous growth and steady diversification of the field were stimulated by the demand for accurate and reliable tools for computational modelling in physical sciences and engineering, and by the rapid development of computer hardware and architecture. At the more theoretical end, the analytical insight into the underlying stability and accuracy properties of computational algorithms for PDEs was deepened by building upon recent progress in mathematical analysis and in the theory of PDEs.

 
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Numerical Analysis 2000 : Linear Algebra - Linear Systems and Eigenvalues (Numerical Analysis 2000)
By C. Brezinski, L. Wuytack, A. Hadjidimos, H.A. van der Vorst



  • Publisher: North Holland
  • Number Of Pages: 544
  • Publication Date: 2000-12-01
  • ISBN-10 / ASIN: 0444505989
  • ISBN-13 / EAN: 9780444505989
  • Binding: Paperback


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With the year 2000 being elected "The World Mathematical Year", the Journal of Computational and Applied Mathematics decided to publish a series of volumes dedicated to various disciplines of applied mathematics and numerical analysis. The series received the ambitious title Numerical Analysis in the 20th Century" and contains seven volumes of which the present one is devoted to "Linear Algebra".

From the early days of scientific computing, numerical linear algebra has been driven by the necessity to be able to solve linear systems, to solve eigenproblems, and to understand the meaning of the results. Because many of these problems have to be solved repeatedly in other computational problems, the algorithms have to be robust and as fast as possible. This has led to much activity, and other than only developing algorithms on demand, the involved research has been equally intellectually challenging as in other sciences. The behavior of algorithms under rounding errors was a great source of inspiration for the further development of perturbation theory.

The papers in this volume can be roughly subdivided into the following groups:

1. Eigenproblems (including SVD). 2. Linear Systems. 3. Miscellaneous problems and 4. Software.


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Numerical Analysis 2000 : Nonlinear Equations and Optimisation (Numerical Analysis 2000)
By L.W. Watson, C. Brezinski, L. Wuytack, M. Bartholomew-Biggs



  • Publisher: North Holland
  • Number Of Pages: 384
  • Publication Date: 2001-01-01
  • ISBN-10 / ASIN: 0444505997
  • ISBN-13 / EAN: 9780444505996
  • Binding: Paperback


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In one of the papers in this collection, the remark that "nothing at all takes place in the universe in which some rule of maximum of minimum does not appear" is attributed to no less an authority than Euler. Simplifying the syntax a little, we might paraphrase this as Everything is an optimization problem. While this might be something of an overstatement, the element of exaggeration is certainly reduced if we consider the extended form: Everything is an optimization problem or a system of equations. This observation, even if only partly true, stands as a fitting testimonial to the importance of the work covered by this volume.

Since the 1960s, much effort has gone into the development and application of numerical algorithms for solving problems in the two areas of optimization and systems of equations. As a result, many different ideas have been proposed for dealing efficiently with (for example) severe nonlinearities and/or very large numbers of variables. Libraries of powerful software now embody the most successful of these ideas, and one objective of this volume is to assist potential users in choosing appropriate software for the problems they need to solve. More generally, however, these collected review articles are intended to provide both researchers and practitioners with snapshots of the 'state-of-the-art' with regard to algorithms for particular classes of problem. These snapshots are meant to have the virtues of immediacy through the inclusion of very recent ideas, but they also have sufficient depth of field to show how ideas have developed and how today's research questions have grown out of previous solution attempts.

The most efficient methods for local optimization, both unconstrained and constrained, are still derived from the classical Newton approach.

As well as dealing in depth with the various classical, or neo-classical, approaches, the selection of papers on optimization in this volume ensures that newer ideas are also well represented.

Solving nonlinear algebraic systems of equations is closely related to optimization. The two are not completely equivalent, however, and usually something is lost in the translation.

Algorithms for nonlinear equations can be roughly classified as locally convergent or globally convergent. The characterization is not perfect.

Locally convergent algorithms include Newton's method, modern quasi-Newton variants of Newton's method, and trust region methods. All of these approaches are well represented in this volume.​


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Numerical Analysis 2000 : Ordinary Differential Equations and Integral Equations (Numerical Analysis 2000, V. 6)
By G. vanden Berghe, G. Monegato



  • Publisher: North Holland
  • Number Of Pages: 558
  • Publication Date: 2001-07-01
  • ISBN-10 / ASIN: 0444506004
  • ISBN-13 / EAN: 9780444506009
  • Binding: Paperback


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This volume contains contributions in the area of differential equations and integral equations. Many numerical methods have arisen in response to the need to solve "real-life" problems in applied mathematics, in particular problems that do not have a closed-form solution. Contributions on both initial-value problems and boundary-value problems in ordinary differential equations appear in this volume. Numerical methods for initial-value problems in ordinary differential equations fall naturally into two classes: those which use one starting value at each step (one-step methods) and those which are based on several values of the solution (multistep methods).

John Butcher has supplied an expert's perspective of the development of numerical methods for ordinary differential equations in the 20th century.

Rob Corless and Lawrence Shampine talk about established technology, namely software for initial-value problems using Runge-Kutta and Rosenbrock methods, with interpolants to fill in the solution between mesh-points, but the 'slant' is new - based on the question, "How should such software integrate into the current generation of Problem Solving Environments?"

Natalia Borovykh and Marc Spijker study the problem of establishing upper bounds for the norm of the nth power of square matrices.

The dynamical system viewpoint has been of great benefit to ODE theory and numerical methods. Related is the study of chaotic behaviour.

Willy Govaerts discusses the numerical methods for the computation and continuation of equilibria and bifurcation points of equilibria of dynamical systems.

Arieh Iserles and Antonella Zanna survey the construction of Runge-Kutta methods which preserve algebraic invariant functions.

Valeria Antohe and Ian Gladwell present numerical experiments on solving a Hamiltonian system of Hénon and Heiles with a symplectic and a nonsymplectic method with a variety of precisions and initial conditions.

Stiff differential equations first became recognized as special during the 1950s. In 1963 two seminal publications laid to the foundations for later development: Dahlquist's paper on A-stable multistep methods and Butcher's first paper on implicit Runge-Kutta methods.

Ernst Hairer and Gerhard Wanner deliver a survey which retraces the discovery of the order stars as well as the principal achievements obtained by that theory.

Guido Vanden Berghe, Hans De Meyer, Marnix Van Daele and Tanja Van Hecke construct exponentially fitted Runge-Kutta methods with s stages.

Differential-algebraic equations arise in control, in modelling of mechanical systems and in many other fields.

Jeff Cash describes a fairly recent class of formulae for the numerical solution of initial-value problems for stiff and differential-algebraic systems.

Shengtai Li and Linda Petzold describe methods and software for sensitivity analysis of solutions of DAE initial-value problems.

Again in the area of differential-algebraic systems, Neil Biehn, John Betts, Stephen Campbell and William Huffman present current work on mesh adaptation for DAE two-point boundary-value problems.

Contrasting approaches to the question of how good an approximation is as a solution of a given equation involve (i) attempting to estimate the actual error (i.e., the difference between the true and the approximate solutions) and (ii) attempting to estimate the defect - the amount by which the approximation fails to satisfy the given equation and any side-conditions.

The paper by Wayne Enright on defect control relates to carefully analyzed techniques that have been proposed both for ordinary differential equations and for delay differential equations in which an attempt is made to control an estimate of the size of the defect.

Many phenomena incorporate noise, and the numerical solution of stochastic differential equations has developed as a relatively new item of study in the area.

Keven Burrage, Pamela Burrage and Taketomo Mitsui review the way numerical methods for solving stochastic differential equations (SDE's) are constructed.

One of the more recent areas to attract scrutiny has been the area of differential equations with after-effect (retarded, delay, or neutral delay differential equations) and in this volume we include a number of papers on evolutionary problems in this area.

The paper of Genna Bocharov and Fathalla Rihan conveys the importance in mathematical biology of models using retarded differential equations.

The contribution by Christopher Baker is intended to convey much of the background necessary for the application of numerical methods and includes some original results on stability and on the solution of approximating equations.

Alfredo Bellen, Nicola Guglielmi and Marino Zennaro contribute to the analysis of stability of numerical solutions of nonlinear neutral differential equations.

Koen Engelborghs, Tatyana Luzyanina, Dirk Roose, Neville Ford and Volker Wulf consider the numerics of bifurcation in delay differential equations.

Evelyn Buckwar contributes a paper indicating the construction and analysis of a numerical strategy for stochastic delay differential equations (SDDEs).

This volume contains contributions on both Volterra and Fredholm-type integral equations.

Christopher Baker responded to a late challenge to craft a review of the theory of the basic numerics of Volterra integral and integro-differential equations.

Simon Shaw and John Whiteman discuss Galerkin methods for a type of Volterra integral equation that arises in modelling viscoelasticity.

A subclass of boundary-value problems for ordinary differential equation comprises eigenvalue problems such as Sturm-Liouville problems (SLP) and Schrödinger equations.

Liviu Ixaru describes the advances made over the last three decades in the field of piecewise perturbation methods for the numerical solution of Sturm-Liouville problems in general and systems of Schrödinger equations in particular.

Alan Andrew surveys the asymptotic correction method for regular Sturm-Liouville problems.

Leon Greenberg and Marco Marletta survey methods for higher-order Sturm-Liouville problems.

R. Moore in the 1960s first showed the feasibility of validated solutions of differential equations, that is, of computing guaranteed enclosures of solutions.

Boundary integral equations. Numerical solution of integral equations associated with boundary-value problems has experienced continuing interest.

Peter Junghanns and Bernd Silbermann present a selection of modern results concerning the numerical analysis of one-dimensional Cauchy singular integral equations, in particular the stability of operator sequences associated with different projection methods.

Johannes Elschner and Ivan Graham summarize the most important results achieved in the last years about the numerical solution of one-dimensional integral equations of Mellin type of means of projection methods and, in particular, by collocation methods.

A survey of results on quadrature methods for solving boundary integral equations is presented by Andreas Rathsfeld.

Wolfgang Hackbusch and Boris Khoromski present a novel approach for a very efficient treatment of integral operators.

Ernst Stephan examines multilevel methods for the h-, p- and hp- versions of the boundary element method, including pre-conditioning techniques.

George Hsiao, Olaf Steinbach and Wolfgang Wendland analyze various boundary element methods employed in local discretization schemes.


 
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Numerical Analysis 2000 : Approximation Theory (Journal of Computational and Applied Mathematics, Volume 121, Numbers 1-2, 1 September 2000)
By L. Wuytack, C. Brezinski, J. Wimp



  • Publisher: North Holland
  • Number Of Pages: 476
  • Publication Date: 2000-10-01
  • ISBN-10 / ASIN: 0444505962
  • ISBN-13 / EAN: 9780444505965
  • Binding: Paperback


Product Description:

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The field of numerical analysis has witnessed many significant developments in the 20th century and will continue to enjoy major new advances in the years ahead. Therefore, it seems appropriate to compile a "state-of-the-art" volume devoted to numerical analysis in the 20th century. This volume on "Approximation Theory" is the first of seven volumes that will be published in this Journal. It brings together the papers dealing with historical developments, survey papers and papers on recent trends in selected areas.

In his paper, G.A. Watson gives an historical survey of methods for solving approximation problems in normed linear spaces. He considers approximation in Lp and Chebyshev norms of real functions and data. Y. Nievergelt describes the history of least-squares approximation. His paper surveys the development and applications of ordinary, constrained, weighted and total least-squares approximation. D. Leviatan discusses the degree of approximation of a function in the uniform of Lp norm.

The development of numerical algorithms is strongly related to the type of approximating functions that are used, e.g. orthogonal polynomials, splines and wavelets, and several authors describe these different approaches.

E. Godoy, A. Ronveaux, A. Zarzo, and I. Area treat the topic of classical orthogonal polynomials R. Piessens, in his paper, illustrates the use of Chebyshev polynomials in computing integral transforms and for solving integral equations.

Some developments in the use of splines are described by G. Nürnberger, F. Zeilfelder (for the bivariate case), and by R.-H. Wang in the multivariate case. For the numercial treatment of functions of several variables, radial basis functions are useful tools. R. Schaback treats this topic in his paper. Certain aspects of the computation of Daubechie wavelets are explained and illustrated in the paper by C. Taswell, P. Guillaume and A. Huard explore the case of multivariate Padée approximation.

Special functions have played a crucial role in approximating the solutions of certain scientific problems. N. Temme illustrates the usefulness of parabolic cylinder functions and J.M. Borwein, D.M. Bradley, R.E. Crandall provide a compendium of evaluation methods for the Riemann zeta function. S. Lewanowicz develops recursion formulae for basic hypergeometric functions. Aspects of the spectral theory for the classical Hermite differential equation appear in the paper by W.M. Everitt, L.L. Littlejohn and R. Wellman.

Many applications of approximation theory are to be found in linear system theory and model reduction. The paper of B. De Schutter gives an overview of minimal state space realization in linear system theory and the paper by A. Bultheel and B. De Moor describes the use of rational approximation in linear systems and control.

For problems whose solutions may have singularities or infinite domains, sinc approximation methods are of value. F. Stenger summarizes the results in this field in his contribution.

G. Alefeld and G. Mayer provide a survey of the historical developoment of interval analysis, including several applications of interval mathematics to numerical computing.

These papers illustrate the profound impact that ideas of approximation theory have had in the creation of numerical algorithms for solving real-world scientific problems. Furthermore, approximation-theortical concepts have proved to be basic tools in the analysis of the applicability of these algorithms.

We thank the authors of the above papers for their willingness to contribute to this volume. Also, we very much appreciate the referees for their role in making this volume a valuable source of information for the next millennium.

 
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Numerical Analysis 2000 : Interpolation and Extrapolation (Journal of Computational and Applied Mathematics, Volume 122, Numbers 1-2, 1 October 2000)
By L. Wuytack, C. Brezinski



  • Publisher: North Holland
  • Number Of Pages: 372
  • Publication Date: 2000-11-01
  • ISBN-10 / ASIN: 0444505970
  • ISBN-13 / EAN: 9780444505972
  • Binding: Paperback


Product Description:


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This volume is dedicated to two closely related subjects: interpolation and extrapolation. The papers can be divided into three categories: historical papers, survey papers and papers presenting new developments.

Interpolation is an old subject since, as noticed in the paper by M. Gasca and T. Sauer, the term was coined by John Wallis in 1655. Interpolation was the first technique for obtaining an approximation of a function. Polynomial interpolation was then used in quadrature methods and methods for the numerical solution of ordinary differential equations.

Extrapolation is based on interpolation. In fact, extrapolation consists of interpolation at a point outside the interval containing the interpolation points. Usually, this point is either zero or infinity. Extrapolation is used in numerical analysis to improve the accuracy of a process depending of a parameter or to accelerate the convergence of a sequence. The most well-known extrapolation processes are certainly Romberg's method for improving the convergence of the trapezoidal rule for the computation of a definite integral and Aiken's &Dgr;2 process which can be found in any textbook of numerical analysis.

Obviously, all aspects of interpolation and extrapolation have not been treated in this volume. However, many important topics have been covered.

 
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