雅可比迭代公式的MATLAB程序

给你一个正确的程序，你自己参考一下吧！

function [x,k]=Jacobimethod(A,b,x0,N,emg)

% A:线性方程组左端矩阵

% b:线性没伍滚方程组右端向量

% x0:迭代初值

% N:迭橘肢代次数上界，若迭代枯余次数大于n，则迭代失败

% emg:精度指标

% k:迭代次数

% x:用迭代法求得的线性方程组的近似解

n=length(A)

x1=zeros(n,1)x2=zeros(n,1)

x1=x0k=0

r=max(abs(b-A*x1))

while r>emg

for i=1:n

sum=0

for j=1:n

if i~=j

sum=sum+A(i,j)*x1(j)

end

end

x2(i)=(b(i)-sum)/A(i,i)

end

r=max(abs(x2-x1))

x1=x2

k=k+1

if k>N

disp('迭代失败，返回')；

return

end

end

祝朋友好运！

function [x, error, iter, flag] = jacobi(A, x, b, max_it, tol)

% jacobi.m solves the linear system Ax=b using the Jacobi Method.

%

% input AREAL matrix

% xREAL initial guess vector

% bREAL right hand side vector

% max_it INTEGER maximum number of iterations

% tol REAL error tolerance

%

% output xREAL solution vector

% errorREAL error norm

% iter INTEGER number of iterations performed

% flag INTEGER: 0 = solution found to tolerance

% 1 = no convergence given max_it

iter = 0 % initialization

flag = 0

bnrm2 = norm( b )

if ( bnrm2 == 0.0 ), bnrm2 = 1.0end

r = b - A*x

error = norm( r ) / bnrm2

if ( error <好棚 tol ) return, end

[m,n]=size(A)

[ M, N ] = split( A , b, 1.0, 1 ) % matrix splitting

for iter = 1:max_it % begin iteration

x_1 = x

x = M \ (N*x + b) % update approximation

error = norm( x - x_1 ) /唤袜做 norm( x ) % compute error

if ( error <和衡= tol )

break

end % check convergence

end

if ( error >tol )

flag = 1

end % no convergence

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