2004 / xvi + 472 pages / Softcover / ISBN: 978-0-898715-57-6 / List Price $110.50 /SIAM Member Price $77.35 / Order Code OT85
"This first book on the numerical analysis of polynomial systems is a stepping stone at the interface of symbolic computation and numerical computation."
-- Bernard Sturmfels, Department of Mathematics, University of Berkeley
"I am not familiar with any books that do such a careful job of combining numerical analysis with the algebra of polynomial equations. Dr. Stetter's book is unique in this regard."
-- David Cox, Department of Mathematics, Amherst College
In many important areas of scientific computing, polynomials in one or more variables are employed in the mathematical modeling of real-life phenomena; yet most of classical computer algebra assumes exact rational data. This book is the first comprehensive treatment of the emerging area of numerical polynomial algebra, an area that falls between classical numerical analysis and classical computer algebra but, surprisingly, has received little attention so far.
The author introduces a conceptual framework that permits the meaningful solution of various algebraic problems with multivariate polynomial equations whose coefficients have some indeterminacy; for this purpose, he combines approaches of both numerical linear algebra and commutative algebra. For the application scientist, Numerical Polynomial Algebra provides both a survey of polynomial problems in scientific computing that may be solved numerically and a guide to their numerical treatment. In addition, the book provides both introductory sections and novel extensions of numerical analysis and computer algebra, making it accessible to the reader with expertise in either one of these areas.
Graduate students or academic and industrial research scientists in numerical analysis and computer algebra can use Numerical Polynomial Algebra as a textbook or reference book. The book is clearly written and standard numerical linear algebra notation is used consistently throughout. Principles and their application are explained through numerical examples and exercises avoiding excessive technical detail. Numerous open-ended problems invite further investigation and research.
Preface; Part I: Polynomials and Numerical Analysis; Chapter 1: Polynomials; Chapter 2: Representations of Polynomial Ideals; Chapter 3: Polynomials with Coefficients of Limited Accuracy; Chapter 4: Approximate Numerical Computation; Part II: Univariate Polynomial Problems; Chapter 5: Univariate Polynomials; Chapter 6: Various Tasks with Empirical Univariate Polynomials; Part III: Multivariate Polynomial Problems; Chapter 7: One Multivariate Polynomial; Chapter 8: Zero-Dimensional Systems of Multivariate Polynomials; Chapter 9: Systems of Empirical Multivariate Polynomials; Chapter 10: Numerical Basis Computation; Part IV: Positive-Dimensional Polynomial Systems; Chapter 11: Matrix Eigenproblems for Positive-Dimensional Systems; Index
Correction to page 422.
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