Pragmatic and Adaptable Textbook Meets the Needs of Students and Instructors from Diverse Fields
Numerical analysis is a core subject in data science and an essential tool for applied mathematicians, engineers, and physical and biological scientists. This updated and expanded edition of Numerical Analysis for Applied Science follows the tradition of its precursor by providing a modern, flexible approach to the theory and practical applications of the field. As before, the authors emphasize the motivation, construction, and practical considerations before presenting rigorous theoretical analysis. This approach allows instructors to adapt the textbook to a spectrum of uses, ranging from one-semester, methods-oriented courses to multi-semester theoretical courses.
The book includes an expanded first chapter reviewing useful tools from analysis and linear algebra. Subsequent chapters include clearly structured expositions covering the motivation, practical considerations, and theory for each class of methods. The book includes over 250 problems exploring practical and theoretical questions and 32 pseudocodes to help students implement the methods. Other notable features include:
* A preface providing advice for instructors on using the text for a single semester course or multiple-semester sequence of courses
* Discussion of topics covered infrequently by other texts at this level, such as multidimensional interpolation, quasi-Newton methods in several variables, multigrid methods, preconditioned conjugate-gradient methods, finite-difference methods for partial differential equations, and an introduction to finite-element theory
* New topics and expanded treatment of existing topics to address developments in the field since publication of the first edition
* More than twice as many computational and theoretical exercises as the first edition.
Numerical Analysis for Applied Science, Second Edition provides an excellent foundation for graduate and advanced undergraduate courses in numerical methods and numerical analysis. It is also an accessible introduction to the subject for students pursuing independent study in applied mathematics, engineering, and the physical and life sciences and a valuable reference for professionals in these areas.
Autorentext
Myron B. Allen III, PhD, is Professor of Mathematics in the Department of Mathematics and Statistics at the University of Wyoming, Laramie, USA. His research focuses on the numerical analysis of fluid flows in porous media.
The Late Eli L. Isaacson, PhD, was Professor Emeritus of Mathematics in the Department of Mathematics at the University of Wyoming, Laramie, USA. His work includes analytic and numerical methods for solving systems of hyperbolic conservation laws, including front-tracking methods.
Inhalt
Preface v
1 Some Useful Tools 1
1.1 Introduction 1
1.2 Bounded Sets 4
1.2.1 The Least Upper Bound Principle 4
1.2.2 Bounded Sets in Rn 5
1.3 Normed Vector Spaces 8
1.3.1 Vector Spaces 8
1.3.2 Matrices as Linear Operators 10
1.3.3 Norms 12
1.3.4 Inner Products 15
1.3.5 Norm Equivalence 17
1.4 Eigenvalues and Matrix Norms 19
1.4.1 Eigenvalues and Eigenvectors 19
1.4.2 Matrix Norms 21
1.5 Results from Calculus 26
1.5.1 Seven Theorems 26
1.5.2 The Taylor Theorem 28
1.6 Problems 33
2 Approximation of Functions 37
2.1 Introduction 37
2.2 Polynomial Interpolation 38
2.2.1 Motivation and Construction 38
2.2.2 Practical Considerations 42
2.2.3 Mathematical Details 43
2.2.4 Further Remarks 46
2.3 Piecewise Polynomial Interpolation 48
2.3.1 Motivation and Construction 48
2.3.2 Practical Considerations 50
2.3.3 Mathematical Details 54
2.3.4 Further Remarks 55
2.4 Hermite Interpolation 55
2.4.1 Motivation and Construction 55
2.4.2 Practical Considerations 59
2.4.3 Mathematical Details 60
2.5 Interpolation in Two Dimensions 63
2.5.1 Constructing Tensor-product Interpolants 64
2.5.2 Error Estimates for Tensor-product Methods 68
2.5.3 Interpolation on Triangles: Background 70
2.5.4 Construction of Planar Interpolants on Triangles 72
2.5.5 Error Estimates for Interpolation on Triangles 74
2.6 Splines 78
2.6.1 Motivation and Construction 78
2.6.2 Practical Considerations 84
2.6.3 Mathematical Details 85
2.6.4 Further Remarks 94
2.7 Least-squares Methods 95
2.7.1 Motivation and Construction 96
2.7.2 Practical Considerations 100
2.7.3 Mathematical Details 101
2.7.4 Further Remarks 103
2.8 Trigonometric Interpolation 104
2.8.1 Motivation and Construction 105
2.8.2 Practical Considerations: Fast Fourier Transform 109
2.8.3 Mathematical Details 116
2.8.4 Further Remarks 118
2.9 Problems 118
3 Direct Methods for Linear Systems 125
3.1 Introduction 125
3.2 The Condition Number of a Linear System 127
3.3 Gauss Elimination 131
3.3.1 Motivation and Construction 131
3.3.2 Practical Considerations 133
3.3.3 Mathematical Details 139
3.4 Variants of Gauss Elimination 148
3.4.1 Motivation 148
3.4.2 The Doolittle and Crout Methods 148
3.4.3 Cholesky Decomposition 152
3.5 Band Matrices 155
3.5.1 Motivation and Construction 155
3.5.2 Practical Considerations 161
3.5.3 Mathematical Details 163
3.5.4 Further Remarks 166
3.6 Iterative Improvement 167
3.7 Problems 169
4 Solution of Nonlinear Equations 175
4.1 Introduction 175
4.2 Bisection 179
4.2.1 Motivation and Construction 179
4.2.2 Practical Considerations 181
4.3 Successive Substitution in One Variable 183
4.3.1 Motivation and Construction 183
4.3.2 Practical Considerations 184
4.3.3 Mathematical Details 190
4.4 Newton's Method in One Variable 192
4.4.1 Motivation and Construction 192
4.4.2 Practical Considerations 194
4.4.3 Mathematical Details 199
4.5 The Secant Method 203
4.5.1 Motivation and Construction 203
4.5.2 Practical Considerations 205
4.5.3 Mathematical Details 206
4.6 Successive Substitution: Several Variables 211
4.6.1 Motivation and Construction 211
4.6.2 Convergence Criteria 213
4.6.3 An Applicat...