數值分析課程設計報告書
Ⅰ 求數值分析課程設計請發郵箱[email protected]
c語言的？
Ⅱ 你好，能幫我解決一個數值分析的課程設計么。謝謝了
冪法是求最大特徵值的吧
你這個得用反冪法的
Ⅲ 數值分析課程設計，編制一般迭代法、牛頓法、弦截法求解方程組的計算機程序，並分析它們的特點
C++才是主流語言。。
你是建模用的嗎？那可根據語法稍加修改，這個編程實現的難度不大。
#include <iostream>//弦截法
using namespace std;
static int count=1;
double f(double x)
{
return (x*x*x-x-1);
}
int main()
{
double x0,x1,x2;
double e=0.00001;
cout<<"請輸入兩個初值X0，X1"<<endl;
cin>>x0>>x1;
x2=x1-f(x1)*(x1-x0)/(f(x1)-f(x0));
while(x2-x1>e||x1-x2>e)
{
x0=x1;
x1=x2;
x2=x1-f(x1)*(x1-x0)/(f(x1)-f(x0));
count+=1;
}
cout<<"方程的根為："<<x2<<endl;
cout<<"迭代的次數為："<<count<<endl;
return 0;
}
#include<iostream>//簡單迭代法
#include<math.h>
using namespace std;
double f(double t0)
{ double t=t0+1;
return pow(t,1.0/3);
}
int main()
{
double a,b,x0,x1,e;
static int count=1;
cout<<"請輸入A，B的值"<<endl;
cin>>a>>b;
cout<<"請輸入E的值"<<endl;
cin>>e;
x0=(a+b)/2;
x1=f(x0);
while((x1-x0)>e||(x0-x1)>e)
{
count+=1;
x0=x1;
x1=f(x0);
}
cout<<"方程的根為："<<x1<<endl;
cout<<"迭代次數"<<count<<endl;
return 0;
}
#include <iostream>//牛頓迭代法
using namespace std;
static k=0;
static int count=1;
double newt(double x)
{
return (x*x*x-x-1);
}
int main()
{
double x0,x1,x2;
cout<<"請輸入兩個初值X0，X1"<<endl;
cin>>x0>>x1;
x2=x1-f(x1)*(x1-x0)/(f(x1)-f(x0));
while(x2-x1>e||x1-x2>e)
{
x0=x1;
x1=x2;
x2=x1-f(x1)*(x1-x0)/(f(x1)-f(x0));
count+=1;
}
cout<<"方程的根為："<<x2<<endl;
cout<<"迭代的次數為："<<count<<endl;
return 0;
}
牛頓迭代法是求方程根的重要方法之一，，方法使用函數f(x)的泰勒級數的前面幾項來尋找方程f(x) = 0的根。其最大優點是在方程f(x) = 0的單根附近具有平方收斂，而且該法還可以用來求方程的重根、復根。另外該方法廣泛用於計算機編程中。
簡單迭代法又稱逐次迭代法，基本思想是構造不動點方程，以求得近似根。即由方程f(x)=0變換為x=F(x), 然後建立迭代格式
弦截法計算x(k+1)時需要利用前兩步信息x(k),x(k-1).免去了Newton法中需要求解一階導函數的繁瑣.
但收斂速度比牛頓法要慢
Ⅳ 用vb做數值分析課程設計
這口氣太狂了，你就一個要代碼的，跟要飯的沒啥兩樣，狂啥？
Ⅳ 數值分析課程設計報告列主元消去發求矩陣行列式的值 及求解線性方程組
你好！具體功能要求發一下，可以嘗試完成
Ⅵ 數值分析課程設計利用多項式擬合和指數函數擬合題
這種東西也拿出來，還只給30分。太不地道了
Ⅶ 課程設計（論文）任務書 脈沖激光放大器增益特性數值分析
參考《激光原理》197頁
Ⅷ 跪求《數值分析》方面的論文或研究報告
1. James W. Cooley and John W. Tukey, "An algorithm for the machine
calculation of complex Fourier series," Mathematics of Computation 19
(1965), 297-301.
2. R. Courant, K. O. Friedrichs and H. Lewy, "Ueber die partiellen
Differenzengleichungen der mathematischen Physik," Mathematische Annalen
100 (1928), 32-74. Translated as: "On the partial difference equations of
mathematical physics," IBM Journal of Resarch and Development 11 (1967),
215-234.
3. A. S. Householder, "Unitary triangularization of a nonsymmetric matrix,"
Journal of the Association of Computing Machinery 5 (1958), 339-342.
4. C. F. Curtiss and J. O. Hirschfelder, "Integration of stiff equations,"
Proceedings of the National Academy of Sciences 38 (1952), 235-243.
5. C. de Boor, "On calculating with B-splines," Journal of Approximation
Theory 6 (1972), 50-62.
6. R. Courant, "Variational methods for the solution of problems of
equilibrium and vibrations," Bulletin of the American Mathematical Society
49 (1943), 1-23.
7. G. Golub and W. Kahan, "Calculating the singular values and pseudo-inverse
of a matrix," SIAM Journal on Numerical Analysis 2 (1965), 205-224.
8. A. Brandt, "Multi-level adaptive solutions to boundary-value problems,"
Mathematics of Computation 31 (1977), 333-390.
9. Magnus R. Hestenes and Eard Stiefel, "Methods of conjugate gradients for
solving linear systems," Journal of Research of the National Bureau of
Standards 49 (1952), 409-436.
10. R. Fletcher and M. J. D. Powell, "A rapidly convergent descent method for
minimization," Computer Journal 6 (1963), 163-168.
11. G. Wanner, E. Hairer and S. P. Norsett, "Order stars and stability
theorems," BIT 18 (1974), 475-489.
12. N. Karmarkar, "A new polynomial-time algorithm for linear programming,"
Combinatorica 4 (1984), 373-395.
13. L. Greengard and V. Rokhlin, "A fast algorithm for particle simulations,"
Journal of Computational Physics 72 (1987), 325-348.