function X=gseid(A,B,P,delta, max1)% Input - A is an N x N nonsingular matrix% - B is an N x 1 matrix% - P is an N x 1 matrix; the initial guess% - delta is the tolerance for P% - max1 is the maximum number of iterations% Output - X is an N x 1 matrix: the gauss-seidel approximation to% the solution of AX = B% NUMERICAL METHODS: Matlab Programs% (c) 2004 by John H. Mathews and Kurtis D. Fink% Complementary Software to accompany the textbook:% NUMERICAL METHODS: Using Matlab, Fourth Edition% ISBN: 0-13-065248-2% Prentice-Hall Pub. Inc.% One Lake Street% Upper Saddle River, NJ 07458N = length(B);for k=1:max1 for j=1:N if j==1 X(1)=(B(1)-A(1,2:N)*P(2:N))/A(1,1); elseif j==N X(N)=(B(N)-A(N,1:N-1)*(X(1:N-1))')/A(N,N); else %X contains the kth approximations and P the (k-1)st X(j)=(B(j)-A(j,1:j-1)*X(1:j-1)'-A(j,j+1:N)*P(j+1:N))/A(j,j); end end err=abs(norm(X'-P)); relerr=err/(norm(X)+eps); P=X'; if (err<delta)|(relerr<delta) break endendX=X';怎么用它来解下面这道题呢
A=diag(ones(1,50)*12);A=A+[[zeros(49,1) -2*diag(ones(1,49))];zeros(1,50)];A=A+[[zeros(1,49); -2*diag(ones(1,49))] zeros(50,1)];A=A+[[zeros(48,2) diag(ones(1,48))];zeros(2,50)];A=A+[[zeros(2,48); diag(ones(1,48))] zeros(50,2)];b=ones(50,1)*5;x=gseid(A,b,zeros(50,1),0.001,1000)
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