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Introduction to Numerical Analysis (Pure & Applied Mathematics), by Francis Begnaud Hildebrand
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The ultimate aim of the field of numerical analysis is to provide convenient methods for obtaining useful solutions to mathematical problems and for extracting useful information from available solutions which are not expressed in tractable forms. This well-known, highly respected volume provides an introduction to the fundamental processes of numerical analysis, including substantial grounding in the basic operations of computation, approximation, interpolation, numerical differentiation and integration, and the numerical solution of equations, as well as in applications to such processes as the smoothing of data, the numerical summation of series, and the numerical solution of ordinary differential equations.
Chapter headings include:
l. Introduction
2. Interpolation with Divided Differences
3. Lagrangian Methods
4. Finite-Difference Interpolation
5. Operations with Finite Differences
6. Numerical Solution of Differential Equations
7. Least-Squares Polynomial Approximation
In this revised and updated second edition, Professor Hildebrand (Emeritus, Mathematics, MIT) made a special effort to include more recent significant developments in the field, increasing the focus on concepts and procedures associated with computers. This new material includes discussions of machine errors and recursive calculation, increased emphasis on the midpoint rule and the consideration of Romberg integration and the classical Filon integration; a modified treatment of prediction-correction methods and the addition of Hamming's method, and numerous other important topics.
In addition, reference lists have been expanded and updated, and more than 150 new problems have been added. Widely considered the classic book in the field, Hildebrand's Introduction to Numerical Analysis is aimed at advanced undergraduate and graduate students, or the general reader in search of a strong, clear introduction to the theory and analysis of numbers.
- Sales Rank: #2436301 in Books
- Published on: 1974-03-08
- Original language: English
- Number of items: 1
- Binding: Hardcover
- 672 pages
Most helpful customer reviews
58 of 59 people found the following review helpful.
Great bargain, still suitable as an introduction
By D. Taylor
This is a reprint of the 1974 2nd edition. So what is Numerical Analysis? It's the down-and-dirty methods of approximation and interpolation of equations that don't have closed-formed mathematical solutions. Just about every real-world problem in material engineering from pipe flow, wing design, convection currents to multivariate econometrics have to resort to numerical approximations. You'll find all the familiar names from your undergrad Math and Physics courses here (Newton, Gauss, Largrange, etc.); however, advanced methods in Numerical Analysis has changed tremendously since this book was published. Since NA is dependent on present computing power, what was once too expensive or unthinkable in the 70s can be done today. However, it's still a great introduction and a great bargain from Dover. The writing style is informal and conversationally peer-to-peer, rather than teacher-to-student. There is no historic consciousness placing methods and men in context. You won't find programming algorithms here (not even Fortran or Pascal). There are probably better books out there for what ever your specific speciality is, but at five times the price of this Dover reprint. You'll will find the old favorites here. The book covers the various finite difference approximations (forward, backward and central differences). It uses the operational approach for these. The later chapters cover splines, continued fraction and iterative methods. More importantly it covers the difference between round-off error v. truncation of divergent series in approximations -- something that still confuses practicing professionals. Be warned there have been many improvements in theory and methods in finite element methods of Fluid Dynamics and other 3D modeling (bezier and NURBS); And, the whole world of Complexity and Chaos theory happened well AFTER this book was published. Calculus and Differential EQs are prerequisite, there's no attempt at introduction in the text.
30 of 30 people found the following review helpful.
Outstanding, but with a limitation
By Victor A. Vyssotsky
Although old, this is still an outstanding introduction to a wide range of topics in numerical analysis. I get impatient with the amount of detail Hildebrand devotes to some topics, but that's because those are topics where I already know the techniques and pitfalls.
However, I have one serious criticism of this book. Hildebrand in very many places drags in the question of inherent errors in input data, but fails to distinguish the different views one must take depending on how one got involved with some topic. In 50+ years of doing numerical analysis and numerical software from time to time, I have come to realize that three quite different issues of inherent error occur.
First, one may be working with scientists or engineers to derive results for a specific problem or set of problems. In this case, one must ask two pertinent questions, and keep asking until one gets clear answers: "How are you getting the input data?" and, "What are you going to do with the results?" Given answers to these two questions, one can do analysis and computation knowing from the start how accurate the input data is likely to be, and how much that matters to the results. Hildebrand pays little attention to the quite complicated problem of how one should do the analysis and programming in those situations.
Second, it may happen that there is no input data from the real world, and hence no inherent error; the input data is conjured up out of whole cloth, as happens in many calculations in "computational physics". In those cases, one wants to produce results that accurately reflect the hypotheses provided by the people with the problem to be solved. Usually, one finds in such cases that the more accurately one can do the computation or analysis, the better one can serve one's users.
Third, and most difficult, is the situation where one is writing a utility routine for use by large numbers of people, most of whom one will never encounter. Everyone who has done much numerical programming faces this issue from time to time. Here the problem is that the users are likely to place absolute faith in the results, even in cases where you, as the implementer of the software or originator of the analysis, may know all too well that the results are unstable with respect to very minor variations in input data. This occurs with monotonous regularity, for example, in routines that manipulate matrices to derive such quantities as eigenvalues and eigenvectors. In my own experience, a high proportion of the actual matrices that users present to "utility packages" are ill-conditioned, and there's a reason for this. If the problem were well-conditioned, it wouldn't be a problem for the scientists or engineers or financial types who need a solution; they would know a priori from experience what the answers are. I have no good answer for how one should think about such "utility software" and neither does Hildebrand. The way I deal with it myself is to ensure that mathematically accurate results are provided even for ill-conditioned problems, and to provide documentation for users that includes the equivalent of: "If you ask this software a stupid question, it will give you a stupid (but correct) answer, so if you are unsure about the stability of your data, please call or visit or email me to discuss your specific problem."
In short, despite the virtues of this book, it doesn't come to grips with the issue of numerical analysis and mathematical computation that I have found causes me more headaches than any other.
5 of 5 people found the following review helpful.
Obviously a little dated, but very high quality
By M. Henri De Feraudy
The quality of the writing is extremely high in this book. It's obvious that the author was a most attentive teacher. It may not have C++ or Matlab code or a lot of the modern techniques.
As an introduction you can't go wrong with this book which is excellent for self-study, especially at the price.
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