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● 第一章 数值分析与科学计算引论(Introduction of numerical analysis and scientific calculation)
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● 1.1 数值分析的对象、作用与特点(The subject, function and characteristics of numerical analysis)
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● 1.2 数值计算的误差( Errors of numerical calculation)
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● 1.3 误差定性分析与避免误差危害(Qualitative analysis of error and avoiding error)
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● 1.4 数值计算中算法设计的技术(Techniques of algorithm design in numerical calculation)
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● 第二章 插值法(Interpolation)
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● 2.1 拉格朗日插值(Lagrange interpolation)
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● 2.2 均差与牛顿插值多项式(Divided difference and Newton’s interpolation polynomial)
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● 2.3 埃尔米特插值(Hermite interpolation)
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● 2.4 分段低次插值(Piecewise linear interpolation)
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● 2.5 三次样条插值(Cubic spline interpolation)
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● 第三章 函数逼近(Function approximation)
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● 3.1 函数逼近的概念(Concepts of function approximation)
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● 3.2 正交多项式(Orthogonal polynomials)
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● 3.3 最佳平方逼近(Least squares approximation)
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● 3.4 曲线拟合的最小二乘法(Discrete least squares approximation of curve fitting)
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● 第四章 数值积分与数值微分(Numerical integration and differentiation)
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● 4.1 数值积分概论(Introduction of numerical differentiation)
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● 4.2 牛顿-科特斯公式(Newton-Cotes formula)
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● 4.3 复合求积公式(Composite quadrature)
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● 4.4 龙贝格求积公式(Romberg integration)
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● 4.5 数值微分( Numerical differentiation)
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● 第五章 解线性方程组的直接方法(Direct methods for solving linear systems)
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● 5.1 引言与预备知识(Direct methods for solving linear systems)
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● 5.2 高斯消去法(Gaussian elimination)
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● 5.3 矩阵三角分解法( Matrix factorization)
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● 第六章 解线性方程组的迭代法(Iterative methods for solving linear systems)
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● 6.1 迭代法的基本概念(Concepts of the iterative method)
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● 6.2 雅可比迭代法与高斯-赛德尔迭代法(Jacobi iteration and Gauss-Seidel iteration)
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● 6.3 超松弛迭代法( Successive Over Relaxation Method)
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● 第七章 非线性方程的数值解法(Numerical solutions of nonlinear equations)
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● 7.1 方程求根与二分法( Solving equations and bisection method)
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● 7.2 不动点迭代法及其收敛性(Iterative method of fixed point and its convergence)
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● 7.3 牛顿法(Newton’s method)
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● 7.4 弦截法与抛物线法(Secant method and parabola method)
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● 第八章 常微分方程初值问题数值解法(Numerical solutions of initial-value problems for ordinary differential equations)
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● 8.1 欧拉公式(Euler’s method)
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● 8.2 龙格-库塔方法( Runge-Kutta method)
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● 8.3 线性多步法(Multistep method)