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线性方程组的分解法——LU分解法

时间:2019-12-30 14:38:05      阅读:68      评论:0      收藏:0      [点我收藏+]

标签:etl   position   transform   size   highlight   ati   func   end   method   

  1.代码

%%LU分解法
function LUDM = LU_Decomposition_method(A,b)
global n;global B;global U;global L;global M;
[n,n] = size(A);
B = [A,b];
R_A = rank(A);R_B = rank(B);
if R_A ~= R_B
    disp(‘方程无解‘);
elseif (R_A == R_B) && (R_A == n)
    disp(‘此方程有唯一解‘);
    M = LU_decomposition(A);
    L = M(:,:,1);U = M(:,:,2);
    matrix1 = [L b];
    Y = Lower_trig_iterative_solution(matrix1);
    matrix2 = [U Y];
    X = Upper_trig_iterative_solution(matrix2);
    disp(‘LU分解中L=‘);
    L
    disp(‘LU分解中U=‘);
    U
else
    disp(‘方程有无穷多组解‘);
end
disp(‘解向量为:‘);
LUDM = X;

%%矩阵的LU分解
    function LUD = LU_decomposition(A)
        [n,n] = size(A);
        M = Elementary_transformation_of_the_lower_triangle(A);
        L = M(:,:,n);U=A;
        for i = 1:1:n-1
            U = M(:,:,i)*U;
        end
        LUD(:,:,1) = L;
        LUD(:,:,2) = U;
    end
%%下三角初等变换
    function ETLT = Elementary_transformation_of_the_lower_triangle(A)
        [n,n] = size(A);
        L = zeros(n,1,n);
        for i = 1:1:n
            for j = 1:1:n
                for k = 1:1:n
                    if j == k
                        L(j,k,i) = 1;
                    end
                end
            end
        end
        for i = 1:1:n-1
            for j = 1:1:n
                for k = 1:1:n
                    if j > k
                        if i == k
                            L(j,k,i) = -A(j,k)/A(k,k);
                        end
                        L(i+1:n,i,n) = -L(i+1:n,i,i);
                    end
                end
            end
            A = L(:,:,i)*A;
        end
        ETLT = L;
    end
%%下三角迭代法
    function LTIS = Lower_trig_iterative_solution(M)
        [m,n] = size(M);
        B  =M(:,1:n-1);ba = M(:,n);
        y = zeros(1,m);
        y(1) = ba(1);
        for i = 2:1:m
            sum = 0;
            for j = 1:1:i-1
                sum = sum+B(i,j)*y(j);
            end
            y(i) = ba(i)-sum;
        end
        LTIS = y‘;
    end
%%上三角迭代法
    function UTIS = Upper_trig_iterative_solution(M)
        [m,n] = size(M);
        B = M(:,1:n-1);ba = M(:,n);
        x = zeros(1,m);
        x(m) =ba(m)/B(m,m);
        for i = m-1:-1:1
            sum = 0;
            for j = i+1:1:m
                sum = sum+B(i,j)*x(j);
            end
            x(i) = (ba(i)-sum)/B(i,i);
        end
        UTIS = x‘;
    end
end

  2.例子

clear all
clc
M = rand(9)
b = reshape(rand(3),9,1)
 
S = LU_Decomposition_method(M,b)

M\b

  结果

M =
  列 1 至 7
    0.5944    0.4709    0.4076    0.4235    0.5181    0.0680    0.6022
    0.0225    0.6959    0.8200    0.0908    0.9436    0.2548    0.3868
    0.4253    0.6999    0.7184    0.2665    0.6377    0.2240    0.9160
    0.3127    0.6385    0.9686    0.1537    0.9577    0.6678    0.0012
    0.1615    0.0336    0.5313    0.2810    0.2407    0.8444    0.4624
    0.1788    0.0688    0.3251    0.4401    0.6761    0.3445    0.4243
    0.4229    0.3196    0.1056    0.5271    0.2891    0.7805    0.4609
    0.0942    0.5309    0.6110    0.4574    0.6718    0.6753    0.7702
    0.5985    0.6544    0.7788    0.8754    0.6951    0.0067    0.3225
  列 8 至 9
    0.7847    0.1917
    0.4714    0.7384
    0.0358    0.2428
    0.1759    0.9174
    0.7218    0.2691
    0.4735    0.7655
    0.1527    0.1887
    0.3411    0.2875
    0.6074    0.0911
b =
    0.5762
    0.6834
    0.5466
    0.4257
    0.6444
    0.6476
    0.6790
    0.6358
    0.9452
此方程有唯一解
LU分解中L=
L =
  列 1 至 7
    1.0000         0         0         0         0         0         0
    0.0379    1.0000         0         0         0         0         0
    0.7155    0.5352    1.0000         0         0         0         0
    0.5261    0.5762  -74.4491    1.0000         0         0         0
    0.2717   -0.1391 -136.4397    1.7669    1.0000         0         0
    0.3008   -0.1074  -74.0359    0.9200    0.6765    1.0000         0
    0.7115   -0.0228   42.5434   -0.5996    0.3838 -141.0829    1.0000
    0.1585    0.6728   -1.3001   -0.0414    0.8852  -70.1396    0.4925
    1.0070    0.2658  -39.5864    0.4476    1.3552   49.3425   -0.3788
  列 8 至 9
         0         0
         0         0
         0         0
         0         0
         0         0
         0         0
         0         0
    1.0000         0
    5.1107    1.0000
LU分解中U=
U =
  列 1 至 7
    0.5944    0.4709    0.4076    0.4235    0.5181    0.0680    0.6022
         0    0.6781    0.8045    0.0748    0.9240    0.2522    0.3640
         0         0   -0.0039   -0.0765   -0.2275    0.0404    0.2903
         0         0         0   -5.8101  -16.7848    3.4944   21.0900
   -0.0000         0         0         0   -1.1550    0.1988    2.6992
    0.0000         0         0         0         0   -0.0074    0.5483
    0.0000   -0.0000         0         0         0         0   76.6535
    0.0000    0.0000         0   -0.0000         0         0         0
   -0.0000   -0.0000         0    0.0000         0         0         0
  列 8 至 9
    0.7847    0.1917
    0.4416    0.7312
   -0.7621   -0.2857
  -57.2283  -20.8735
   -2.2924   -1.7782
   -1.9343    0.0429
 -274.3037    6.4447
   -1.9999   -0.0598
         0    0.7768
解向量为:
S =
   -0.9496
    2.2130
    0.5483
    1.9595
   -3.8859
   -0.4632
    0.4453
    0.3978
    2.6573
ans =
   -0.9496
    2.2130
    0.5483
    1.9595
   -3.8859
   -0.4632
    0.4453
    0.3978
    2.6573
>> 

  

线性方程组的分解法——LU分解法

标签:etl   position   transform   size   highlight   ati   func   end   method   

原文地址:https://www.cnblogs.com/guliangt/p/12119385.html

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