coding in matlab 3. Write a function to solve Ax = b using the Jacobi iterative

Question

coding in matlab

3. Write a function to solve Ax = b using the Jacobi iterative method. The function should take in the following as inputs: a matrix A of sizen x n . a vector b of size n × 1 a number et that specifies the total relative squared error tolerance the maximum number of iterations to attempt kmaz The outputs of the function should be: a status variable that indicates whether the solution did or did not converge within kmaz iterations the solution vector x ] The function should iterate until the total estimated squared error summed across all elements is less hantheoln ereotl clidor i den

Explanation / Answer

n=input('dimension of the matrix)

function x1 = jacobi2(a,b,x0,tol)
for(i=1;i<=n;i++)
x(i)=0;
for(itr=1:maxit)
  big=0;
  for(i=1:n)
  

   sum=0;
   for(j=1:n)
   
      if(!i=j)
         sum=sum+a(i,j)*x(j);
     end
                         end
   temp=(a(i,n+1)-sum)/a(i,i)
   relerror=norm((x(i)-temp)*(x(i)-temp)/temp);
   if(relerror>big)
      big=relerror;
                        end
   x(i)=temp;
  end
                end
  
if(big<=e)

  fprintf("Converges to a solution in %d iterations ");
  for(i=1:n)
  x(i)
                end
                else
                fprintf("does not converge in %d iteration ",maxit);
                end

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