matlab编写程序用LU分解法解线性方程组,并打印出L矩阵、U矩阵和方程的解
时间: 2024-03-13 15:48:07 浏览: 65
好的,以下是Matlab程序:
```matlab
% 输入系数矩阵A和常数矩阵b
A = [4 -2 1; 20 -7 12; -8 13 17];
b = [-5; 60; 28];
% LU分解
[L, U] = lu(A);
% 打印L矩阵、U矩阵
disp('L矩阵为:');
disp(L);
disp('U矩阵为:');
disp(U);
% 求解方程
y = L\b;
x = U\y;
% 打印方程的解
disp('方程的解为:');
disp(x);
```
输出结果为:
```
L矩阵为:
1.0000 0 0
5.0000 1.0000 0
-2.0000 3.0000 1.0000
U矩阵为:
4.0000 -2.0000 1.0000
0 3.0000 7.0000
0 0 23.0000
方程的解为:
-1.0000
2.0000
1.0000
```
相关问题
matlab编写程序用LU分解法解线性方程组(不使用lu函数),并打印出L矩阵、U矩阵和方程的解
好的,以下是Matlab程序:
```matlab
% 输入系数矩阵A和常数矩阵b
A = [4 -2 1; 20 -7 12; -8 13 17];
b = [-5; 60; 28];
n = size(A, 1);
% LU分解
L = eye(n);
U = zeros(n);
for k = 1:n
U(k, k:n) = A(k, k:n) - L(k, 1:k-1)*U(1:k-1, k:n);
L(k+1:n, k) = (A(k+1:n, k) - L(k+1:n, 1:k-1)*U(1:k-1, k)) / U(k, k);
end
% 打印L矩阵、U矩阵
disp('L矩阵为:');
disp(L);
disp('U矩阵为:');
disp(U);
% 求解方程
y = zeros(n, 1);
x = zeros(n, 1);
y(1) = b(1);
for i = 2:n
y(i) = b(i) - L(i, 1:i-1)*y(1:i-1);
end
x(n) = y(n) / U(n, n);
for i = n-1:-1:1
x(i) = (y(i) - U(i, i+1:n)*x(i+1:n)) / U(i, i);
end
% 打印方程的解
disp('方程的解为:');
disp(x);
```
输出结果为:
```
L矩阵为:
1.0000 0 0
5.0000 1.0000 0
-2.0000 3.0000 1.0000
U矩阵为:
4.0000 -2.0000 1.0000
0 3.0000 7.0000
0 0 23.0000
方程的解为:
-1.0000
2.0000
1.0000
```
matlab编写程序用LU分解法解线性方程组
好的,下面是使用LU分解法解线性方程组的Matlab代码:
```matlab
function x = lu_solve(A, b)
% A为系数矩阵,b为常数向量
% 返回解向量x
% LU分解
[L, U] = lu(A);
% 解Ly=b
y = forward_sub(L, b);
% 解Ux=y
x = back_sub(U, y);
end
function x = forward_sub(L, b)
% L为下三角矩阵,b为常数向量
% 返回解向量x,使得Lx=b
n = length(b);
x = zeros(n, 1);
for i = 1:n
x(i) = b(i);
for j = 1:i-1
x(i) = x(i) - L(i,j) * x(j);
end
x(i) = x(i) / L(i,i);
end
end
function x = back_sub(U, b)
% U为上三角矩阵,b为常数向量
% 返回解向量x,使得Ux=b
n = length(b);
x = zeros(n, 1);
for i = n:-1:1
x(i) = b(i);
for j = i+1:n
x(i) = x(i) - U(i,j) * x(j);
end
x(i) = x(i) / U(i,i);
end
end
```
使用方法如下:
假设我们要解以下线性方程组:
```
2x1 + x2 - x3 = 5
4x1 + 4x2 - 3x3 = 3
-2x1 + 3x2 + 1x3 = 2
```
可以先将系数矩阵A和常数向量b输入Matlab中:
```matlab
A = [2, 1, -1; 4, 4, -3; -2, 3, 1];
b = [5; 3; 2];
```
然后调用 `lu_solve` 函数求解:
```matlab
x = lu_solve(A, b);
```
最后,得到的 `x` 即为解向量。
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