一、基本概念 Fourier级数定义:设f(x)是(-∞,+∞)上以2为周期的函数,且f(x)在[-n,]上绝对可积,称形如

一、判断题:(8×2分=16分) (1)若x为f的极值点,则x为f的稳定点。()

Prob. 4.2- bolt restart Digits: =4: Diameter. initial force area >d:=.008:F[0]:=1000:A:=Pi*d^2/4: Initial stress sigma [0]: = evalf(F [O]/A)i 989108 Modulus: functio

Property relation Functions F and G Partial molar quantities Property relation derived from U, H, F, and G etc

Second law Functions F and G Property relation Property relation derived from U, H, F, and G etc

1.设函数F(x,y)满足 (1)在区域D:x-a≤x≤x+a,yo-b≤y≤yo+b上连续; (2)F(x0,y)=0

Algorithms Day 40 L23.2 Recall from Lecture 22 • Flow value: | f | = f(s, V). Cut: Any partition (S, T) of V such that s ∈ S and t ∈ T

5.1.1线性空间上的线性函数的定义 1、线性函数的定义 定义设V为数域K上的线性空间,fV→K为映射,满足f(a+B)=f(a)+f(),va,B∈V;f(ka)kf(a),∈k,aev,则称f为由V到K的一个线性函数(即f为V到K的一个线性映射)如同一般的线性映射,有以下事实:

1.设f(x,y)在点M(x,yo)可微,=i-j,u=-i+2如果 af(x,yo)=-2,=1,则f(x,y)在点M(x,)的微分是( af(xo,yo) )

2.5 Hermite插值 插值方法 NewtonLagrange与插值的不足 y=f(x),其 NewtonLagrange与插值多项式Pn(x)与Nn(x) 满足插值条件:P(xi)=nn(xi)=f(x)i=0,12.n Newton与 Lagrange插值多项式与y=f(x)在插值节点上有相同 的函数值“过点” 但在插值节点上y=f(x)与y=Pn(x)一般不”相切”, f(xi)≠n(x)光滑性较差 Hermite插值:求与y=f(x)在插值节点X1.n上具有相同函数 值及导数值(甚至高阶导数值)的插值多项式