Introduced forward_substitution()
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@ -1,5 +1,5 @@
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% Argorithm 4: Back Substitution (Alg. 3.1.2)
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function back_substitution(U,b)
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function b = back_substitution(U,b)
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[n, m] = size(U);
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if n ~= m
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@ -14,9 +14,9 @@ if det(U) == 0
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error('Matrix is not nonsingular!')
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end
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b(n) = b(n)/U(n, n)
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b(n) = b(n)/U(n, n);
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for i = n-1:-1:1
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b(i) = (b(i) - U(i, i+1 : n)*b(i+1 : n))/U(i, i)
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b(i) = (b(i) - U(i, i+1 : n)*b(i+1 : n))/U(i, i);
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end
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end
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@ -0,0 +1,17 @@
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% Algorithm 3: Forward Substitution (Alg. 3.1.1)
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function b = forward_substitution(L, b)
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[n, m] = size(L);
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if n ~= m
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error('Matrix is not squared!')
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end
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if length(b) ~= n
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error('Vector b has wrong length!')
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end
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b(1) = b(1)/L(1,1);
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for i = 2:n
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b(i) = (b(i) - L(i, 1:i-1)*b(1:i-1))/L(i, i);
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end
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@ -1,4 +1,4 @@
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function gaussian_elimination_with_complete_pivoting(A)
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function A = gaussian_elimination_with_complete_pivoting(A)
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% det(A(mi, lm))
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@ -8,23 +8,24 @@ if n ~= m
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end
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if det(A) == 0
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error('Matrix is not nonsingular!')
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error('Matrix is not nonsingular!')
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end
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for k = 1 : n-1
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i = k:n;
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j = k:n;
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A(i, j);
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maximum = max(abs(A(i, j)), [], 'all')
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max_idx = find(abs(A==maximum))
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[mi, lm] = ind2sub(size(A), max_idx(1))
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A(k, 1:n) = A(mi, 1:n)
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A(1:n, k) = A(1:n, lm)
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p(k) = mi
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q(k) = lm
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maximum = max(abs(A(i, j)), [], 'all');
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max_idx = find(abs(A==maximum));
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[mi, lm] = ind2sub(size(A), max_idx(1));
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A([k mi], 1:n) = deal(A([mi k], 1:n));
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A(1:n, [k lm]) = deal(A(1:n, [lm k]));
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p(k) = mi;
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q(k) = lm;
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% Perform Gaussian elimination with the greatest pivot
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if A(k, k) ~= 0
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rows = k+1 : n
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A(rows, k) = A(rows, k)/A(k, k)
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A(rows, rows) = A(rows, rows) - A(rows, k) * A(k, rows)
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rows = k+1 : n;
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A(rows, k) = A(rows, k)/A(k, k);
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A(rows, rows) = A(rows, rows) - A(rows, k) * A(k, rows);
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end
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end
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end
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@ -1,8 +1,10 @@
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clear all;
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B = [2, -1, 0, 0; -1, 2, -1, 0;0, -1, 2, -1; 0, 0, -1, 2]
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B = [2, -1, 0, 0; -1, 2, -1, 0;0, -1, 2, -1; 0, 0, -1, 2];
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b = [0;0;0;5]
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b = [0;0;0;5];
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[U, Mk] = outer_product_gaussian_elimination(B)
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back_substitution(U, b)
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[U, Mk] = outer_product_gaussian_elimination(B);
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back_substitution(U, b);
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A = gaussian_elimination_with_complete_pivoting(B);
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@ -10,14 +10,11 @@ end
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error('Matrix is not nonsingular!')
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end
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A;
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for k = 1 : n-1
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rows = k + 1 : n;
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A(rows, k) = A(rows, k)/A(k, k);
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A(rows, rows) = A(rows, rows) - A(rows, k) * A(k, rows);
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A;
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end
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U = triu(A)
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Mk = diag(A,-1) % Gauss vector
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U = triu(A);
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Mk = diag(A,-1); % Gauss vector
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