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An Introduction to Numerical Analysis
 
 
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An Introduction to Numerical Analysis [Paperback]

Endre Süli (Author), David F. Mayers (Author)
4.0 out of 5 stars  See all reviews (4 customer reviews)

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Book Description

0521007941 978-0521007948 September 8, 2003
This textbook is written primarily for undergraduate mathematicians and also appeals to students working at an advanced level in other disciplines. The text begins with a clear motivation for the study of numerical analysis based on real-world problems. The authors then develop the necessary machinery including iteration, interpolation, boundary-value problems and finite elements. Throughout, the authors keep an eye on the analytical basis for the work and add historical notes on the development of the subject. There are numerous exercises for students.

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Editorial Reviews

Review

"This book is a solid text in the basics of numerical mathematics, using more of a theoretical background than most. If you are looking for a book to use in a course in numerical analysis where there is an emphasis on the theoretical background, then this one will serve your needs." Journal of Recreational Mathematics

"carefully written with a good level of rigor" SIAM Review

Book Description

This textbook is written primarily for undergraduate mathematicians but it will also appeal to students working at an advanced level in other disciplines. The text begins with a clear motivation for the study of numerical analysis based on real world problems. The authors then develop the necessary machinery including iteration, interpolation, boundary value problems and finite elements. Throughout, the authors keep an eye on the analytical basis for the work and add interest with historical notes on the development of the subject. There are numerous exercises for students.

Product Details

  • Paperback: 444 pages
  • Publisher: Cambridge University Press (September 8, 2003)
  • Language: English
  • ISBN-10: 0521007941
  • ISBN-13: 978-0521007948
  • Product Dimensions: 9 x 5.8 x 0.9 inches
  • Shipping Weight: 1.6 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Best Sellers Rank: #138,058 in Books (See Top 100 in Books)

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Customer Reviews

4 Reviews
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 (2)
4 star:
 (1)
3 star:    (0)
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Average Customer Review
4.0 out of 5 stars (4 customer reviews)
 
 
 
 
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7 of 7 people found the following review helpful:
5.0 out of 5 stars Numerical analysis focusing on foundation, September 15, 2006
This book has emphasis on analysis of numerical methods, including
error bound, consistency, convergence, stability. In most cases, a
numerical method is introduced, followed by analysis and proofs. For
engineering students, who like to know more algorithms and a little
bit of analysis, this book may not be the best choice.

Although this book is mainly about analysis, it does include clear
presentation of many numerical methods, including topics in nonlinear
equations solving, numerical linear algebra, polynomial interpolation
and integration, numerical solution of ODE. In numerical linear
algebra, it includes LU factorization with pivoting, Gerschgorin's
theorem of eigenvalue positions, Calculating eigenvalues by Jacobi
plane rotation, Householder tridiagonalization, Sturm sequence
property for tridiagonal symmetric matrix. Interpolation includes
Lagrange polynomial, Hermite polynomial, Newton-Cotes integration,
Improved Trapezium integration through Romberg method, Oscillation
theorem for minimax approximation, Chebyshev polynomial, least square
polynomial approximation to a known function, Gauss quadrature using
Hermite polynomial, Piecewise linear/cubic splines. Ordinary
ddifferential equations section includes initial value problems with
one-step and multiple steps, boundary value problems using finite
difference and shooting method, Galerkin finite element method.
The book gives basic definitions including norms, matrix condition
numbers, real symmetric positive definite matrix, Rayleigh quotient,
orthogonal polynomials, stiffness, Sobolev space.

One place that is not clear is about QR algorithm for tridiagonal
matrix.

In summary, the book is written clearly. Every numerical method is
presented based on mathematics. There are many proofs (there is one
proof with more than 3 pages), most of them that I decided to read are
pretty easy to follow. There are not much implementation details and
tricks. But this book will tell you when a method will converge and
when a method is better. As a non-math major reader, I wish it could
present more algorithms, such as algorithms for eigenvalues of
nonsymmetric matrix, more details in finite difference method, a
little bit of partial differential equations etc.
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4 of 4 people found the following review helpful:
4.0 out of 5 stars A textbook for the theory of numerical analysis, July 21, 2004
This review is from: An Introduction to Numerical Analysis (Paperback)
Many people naively believe that with the growing power of symbolic mathematics packages such as Mathematica?, knowledge in numerical analysis is increasingly irrelevant. That is not true, all programmers should have some knowledge of numerical techniques and even power users of a symbolic mathematics package should have some theoretical knowledge in numerical techniques. The packages will perform operations such as polynomial interpolation and at the very least a user should know when to use a specific type.
This book is a solid text in the basics of numerical mathematics, using more of a theoretical background than most. There are a large number of theorem-proof instances, so in that respect, it resembles a math book. The material covered is:

* Solutions of linear equations and systems of linear equations.
* Matrices, eigenvalues and eigenvectors.
* Polynomial interpolation and polynomial approximation.
* Numerical integration.
* Initial value and boundary value problems for ODEs.
* The finite element method.

There are a small number of exercises at the end of each chapter and no solutions are included.
If you are looking for a book to use in a course in numerical analysis where there is an emphasis on the theoretical background, then this one will serve your needs.
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2 of 2 people found the following review helpful:
5.0 out of 5 stars Great textbook, great reference, October 15, 2009
This review is from: An Introduction to Numerical Analysis (Paperback)
This book was used for a one semester course in numerical analysis. The companion
book was Numerical Linear Algebra. Together, these books make an
outstanding start to a personal numerical analysis reference shelf.

The first half of the book is where pure math students may find trouble since the
presentation of linear algebra in math departments varies widely. A practical working
knowledge of basic linear algebra is necessary. A poor linear algebra background will
require remediation before starting this book.

Topics covered in this text that I have found particularly useful over the years
include polynomial interpolation and quadrature. The presentation is perfect and easy
to understand.

Of course, no text can be everything to everyone. It helps to have an enthusiastic and
knowledgeable professor leading you through the material. That said, the dedicated
student should have no problem navigating this text.
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Inside This Book (learn more)
First Sentence:
Equations of various kinds arise in a range of physical applications and a substantial body of mathematical research is devoted to their study. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
composite trapezium rule, polynomials cps, minimax polynomial, local condition number, linear multistep method, subordinate matrix norm, minimax approximation, posteriori error bound, monotone matrices, nonsingular lower triangular matrix, closed real interval, unit lower triangular, symmetric tridiagonal matrix, six decimal digits, leading principal submatrix, single nonlinear equation, simultaneous iteration, three decimal digits, bisection process, interpolation points, consecutive roots, quadrature points, interpolation polynomial, tridiagonal form, bilinear functional
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Cambridge University Press, Oscillation Theorem, Mean Value Theorem, Proof Let, Picard's Theorem, Root Condition, Contraction Mapping Theorem, Rolle's Theorem, Proof Suppose, Brouwer's Fixed Point Theorem, Maximum Principle, Weierstrass Theorem, Acta Numerica, American Mathematical Society, Clarendon Press, John Wiley, Oxford University Press, Third Edition, Academic Press, Augustin-Louis Cauchy, Backward Differentiation Formulae, Englewood Cliffs, Holy Roman Empire
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