数值分析随计算机的发展和使用逐渐受到科学计算工作者的广泛重视，是一种如何利用计算机解决数学问题的近似方法。随科技发展和各种行业迅速崛起的需要，高效的计算方法与高性能并行计算机硬件的需要同等受到当前科学研究的重视。科学计算己与实验、理论分析共同成为现在科学研究的三大重要手段。数值计算的核心是给出和研究各种数学问题的高效而稳定的算法，包括算法的收敛和稳定性讨论。本书主要为高校理工科研究生专业开设的“数值分析或计算方法”双语课程编写的教材，重点介绍常用数值计算方法及相关概念和理论。
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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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