% Define the input matrices A_matrix and B A = [0 0 -1 3 -1 0; 0 1/2 0 -1 3 -1; 1/2 0 0 0 -1 3; 3 -1 0 0 0 1.2; -1 3 -1 0 1/2 0; 0 -1 3 -1 0 0]; B = [1; 3/2; 5/2; 5/2; 3/2; 1]; % Define the Gauss-Seidel function function [X] = GaussSeidel(A, b, tol, max_iter) % Get the dimensions of A and initialize the output vector [n, ~] = size(A); X = zeros(n, 1); X_new = X; tolerance = 1e-3; max_iterations = 1000; X1 = GaussSeidel(A_matrix, B, tolerance, max_iterations); disp(X1); % Iterate through the Gauss-Seidel method for iter = 1:max_iter for i = 1:n X_new(i) = (b(i) - A(i, 1:i-1) * X_new(1:i-1) - A(i, i+1:end) * X(i+1:end)) / A(i, i); end % Check for convergence if norm(X_new - X) < tol break; end % Update the approximation X = X_new; tolerance = 1e-3; max_iterations = 1000; X1 = GaussSeidel(A_matrix, B, tolerance, max_iterations); disp(X1); end end % Set the tolerance and maximum number of iterations; % Call the Gauss-Seidel function with the input matrices and parameters % Display the output

There are a few issues with the code provided. Here's a corrected version:

% Define the input matrices A and B
A = [0 0 -1 3 -1 0; 0 1/2 0 -1 3 -1; 1/2 0 0 0 -1 3; 3 -1 0 0 0 1.2; -1 3 -1 0 1/2 0; 0 -1 3 -1 0 0];
B = [1; 3/2; 5/2; 5/2; 3/2; 1];

% Define the Gauss-Seidel function
function [X] = GaussSeidel(A, b, tol, max_iter)
    % Get the dimensions of A and initialize the output vector
    [n, ~] = size(A);
    X = zeros(n, 1);

    % Iterate through the Gauss-Seidel method
    for iter = 1:max_iter
        X_new = X; % Store the current approximation
        for i = 1:n
            X_new(i) = (b(i) - A(i, 1:i-1) * X_new(1:i-1) - A(i, i+1:end) * X(i+1:end)) / A(i, i);
        end
        
        % Check for convergence
        if norm(X_new - X) < tol
            break;
        end
        
        X = X_new; % Update the approximation
    end
end

% Call the Gauss-Seidel function with the input matrices and parameters
tolerance = 1e-3;
max_iterations = 1000;
X1 = GaussSeidel(A, B, tolerance, max_iterations);

% Display the output
disp(X1);

This code defines the input matrices `A` and `B`, and then defines the `GaussSeidel` function to perform the Gauss-Seidel method. The function takes in the input matrix `A`, the right-hand side vector `b`, a tolerance `tol`, and a maximum number of iterations `max_iter`. It initializes the output vector `X` to be a vector of zeros with the same dimensions as `b`, and then iterates through the Gauss-Seidel method until convergence is reached (i.e., the norm of the difference between the current and previous approximations is less than `tol`). At each iteration, it updates the approximation using the formula for Gauss-Seidel, and then checks for convergence. Finally, it returns the approximation `X`.

The code then calls the `GaussSeidel` function with the input matrices `A` and `B`, a tolerance of `1e-3`, and a maximum of `1000` iterations, and stores the output in `X1`. Finally, it displays the output.