呵呵现在任给一函数f(x),我们怎么知道小波级数可以无限逼近这个函数呢 我们想象任给beta>0,可以将f(x)曲线按每beta长度分成很多小段,对应很多点 若我们可以用一函数g(x)来拟合这些点,那么g(x)和(x)在任意x上的误差将小于beta 若点数量为2^n个那么我们就可以分别用^(n-1)个L波和2^(n-1)个H波拟合 然后可将L波再分解,最后得到一棵树(分解的级数由你决定)

1.1R\的极限理论 在线性代数中我们学习了n维向量空间V={x1…x)x,∈R,1=1,…,n我们在 V,中定义了加法和数乘.特别的我们还定义了V,中的内积(,) 设x=(x1…xn),y=(1…,yn)是V中的向量,定义x与y的内积(x,y)为

§1 the introduction of practical problem §3 the triangular decomposition of matrixs §4 the chasing method §5 the norm of matrixs and vectors §6 the conditions and error analyses about system of linear equations §2 the gauss elimination method

Section1 the Introduction of Practical Problem Section3 Newton—Cotes Quadrature Formula Section4 Compound Multiplicative Section2 Mechanical Quadrature Method and Algebraic Precision Section5 Romberg Quadrature Formula Section6 Gaussian Quadrature Formula Section7 Numerical Differentiation

教学目的： 掌握弱收敛与弱 * 收敛的概念和基本性质。 授课要点： 1 序列弱收敛的定义和基本性质。 2 序列弱 * 收敛的定义和基本性质。 3 强弱序列有界性，闭性，完备性，紧性的比较

1 Mathematical Preliminaries and Error Analysis 2 Solutions of Equations in One Variable 3 Interpolation and Polynomial Approximation 4 Numerical Differentiation and Integration 5 Initial-Value Problems for Ordinary Differential Equations 6 Direct Methods for Solving Linear Systems 7 IterativeTechniques in Matrix Algebra 8 ApproximationTheory 9 Approximating Eigenvalues 10 Numerical Solutions of Nonlinear Systems of Equations 11 Boundary-Value Problems for Ordinary Differential Equations 12 Numerical Solutions to Partial Differential Equations

一、计算题(每题6分,共12分) 1、求矢量方程的导矢F(t),其中r(t)=asinti+bsintj+ccostk. 2、求曲线x=asin2t,y=asin2t,z= cost(>0)在t=处的切向单位矢量

Example 1.6. Consider the graph y(x) cos(x) over [0.0, 1.2]. (a) Use the nodes xo=0.0andx1=1.2 to construct linear interpolating polynomial Pi(). (b)Use the nodes xo 0.2 and x =1.0 to construct a linear approximating polynomial()

当精确函数y=f(x)非常复杂或未知时,在一系列节点xoxn处测得函数值yo=fo) yn=f(xn,由此构造一个简单易算的近似函 数g(x)f(x),满足条件g(x)=f(x(i0 n)。这里的g(x)称为f(x)的插值函数

幂法 Power Method 计算矩阵的主特征根及对应的特征向量 原始幂法/ the original method 条件:A有特征根>+22…=0,对应n个线性无