數值分析隨計算機的發展和使用逐漸受到科學計算工作者的廣泛重視，是一種如何利用計算機解決數學問題的近似方法。隨科技發展和各種行業迅速崛起的需要，高效的計算方法與高性能并行計算機硬件的需要同等受到當前科學研究的重視。科學計算己與實驗、理論分析共同成為現在科學研究的三大重要手段。數值計算的核心是給出和研究各種數學問題的高效而穩定的算法，包括算法的收斂和穩定性討論。本書主要為高校理工科研究生專業開設的“數值分析或計算方法”雙語課程編寫的教材，重點介紹常用數值計算方法及相關概念和理論。
主持國家重點研發項目子課題 1項，國自然科學面上項目
2 項，江蘇省自然科學項目 1項，江蘇省高校自然科學項目 1項
Contents
Preface
Chapter 1 Mathematical Review and Error Analysis 1
1.1 Mathematical Review 1
1.2 Errors and Significant Digits 3
1.2.1 Truncation Error and Round-off Error 4
1.2.2 Absolute Error and Relative Error 5
1.2.3 Significant Digits 6
1.3 Avoid the Loss of Accuracy 8
1.3.1 Avoid the Subtraction of Nearly Equal Numbers.8
1.3.2 Avoid Big Numbers “Swallowing” Small Numbers 9
1.3.3 Reduce Computations 9
1.3.4 Avoid Dividing by a Number with Small Absolute Value 10
1.3.5 Use Stable Algorithms 10
1.4 Exercises 11
Chapter 2 Solutions of Equations in One Variable 13
2.1 The Bisection Method 13
2.2 Fixed-Point Iteration 15
2.2.1 Basic Concepts 15
2.2.2 Convergence and Error Estimation 16
2.2.3 Local Convergence and Order of Convergence 19
2.3 Newton’s Method and Secant Method 21
2.3.1 Newton’s Method 21
2.3.2 Secant Method 23
2.3.3 Newton’s Method for Finding Multiple Roots 24
2.4 Acceleration Techniques 28
2.5 Programs 31
2.6 Exercises 34
Chapter 3 Interpolation 36
3.1 Lagrange Interpolation 36
3.2 Newton Interpolation 41
3.3 Aitken’s Method 47
3.4 Hermite Interpolation 49
3.5 Piecewise Polynomial Interpolation 52
3.6 Cubic Spline Interpolation 53
3.7 Programs 58
3.8 Exercises.60
Chapter 4 Curve Fitting and Orthogonal Polynomials 63
4.1 Least Square Method 63
4.2 Least Square Approximation 70
4.3 Orthogonal Polynomials.73
4.4 Programs 79
4.4.1 Least Square Method 79
4.4.2 Least Square Approximation 79
4.5 Exercises 80
Chapter 5 Direct Methods for Linear Systems .82
5.1 Gaussian Elimination Method 82
5.1.1 Linear Systems of Equation 82
5.1.2 Gaussian Elimination with Backward-Substitution 83
5.2 Gaussian Elimination with Partial Pivoting 87
5.3 Matrix Factorization 90
5.4 Two Special Types of Matrices 96
5.5 Gaussian Elimination on Tridiagonal Linear Systems 99
5.6 Norms of Vectors and Matrices 101
5.6.1 Norms of Vectors 101
5.6.2 Norms of Matrices 102
5.7 Ill-Conditioned Linear System and Condition Number 104
5.8 Programs 106
5.9 Exercises 109
Chapter 6 Iterative Methods for Linear Systems 112
6.1 Iterative Methods 112
6.1.1 Jacobi Iterative Method.112
6.1.2 Gauss-Seidel Iterative Method 116
6.1.3 SOR Method.120
6.2 Convergence Analysis for Iterative Methods 123
6.3 Programs 126
6.4 Exercises 129
Chapter 7 Numerical Differentiation and Integration 132
7.1 Numerical Differentiation 132
7.1.1 Three-Point Formulas and Five-Point Formulas 132
7.1.2 The Method by Using Cubic Spline Interpolating Function 135
7.1.3 Varying Step Size Midpoint Method 135
7.1.4 Richardson Extrapolation 137
7.2 Elements of Numerical Integration 139
7.3 Newton-Cotes Quadrature Formulas.143
7.3.1 Basic Concepts of Newton-Cotes Quadrature Formulas 143
7.3.2 Some Common Newton-Cotes Formulas 145
7.4 Composite Numerical Integration 146
7.5 Romberg Integration 151
7.5.1 Recursive Trapezoidal Rule 151
7.5.2 Romberg Integration 154
7.6 Gaussian Quadrature 156
7.6.1 Basic Concepts 156
7.6.2 Two Common Gaussian Quadrature Formulas 160
7.6.3 Stability and Convergence 163
7.7 Programs 164
7.8 Exercises 170
Chapter 8 Numerical Solutions of Ordinary Differential Equations 172
8.1 Elements of Initial Problems 172
8.2 Euler Method and Modified Euler Method 173
8.2.1 Euler Method and Trapezoidal Method.173
8.2.2 Modified Euler Method 175
8.2.3 Local Truncation Error 176
8.3 Runge-Kutta Methods 178
8.3.1 Second-Order Runge-Kutta Methods 178
8.3.2 Some Common Third-and Fourth-Order Runge-Kutta Methods 181
8.4 Stability and Convergence 183
8.5 Multistep Methods 189
8.6 Programs 192
8.7 Exercises 196
Chapter 9 Approximating Eigenvalues and Eigenvectors 199
9.1 Fundamental Theorems 199
9.2 The Power Method 204
9.3 Accelerating Convergence 208
9.4 Inverse Power Method 209
9.5 Householder’s Method 212
9.6 The QR method 218
9.7 Programs 226
9.8 Exercises 228
References 231
Appendix A English-Chinese Math Key Words 232
Appendix B Some Math Expressions and Pronunciations 239
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