The LU decomposition "A = L U" of the given matrix is:
"\\begin{pmatrix}\n1 & -1 & 4 \\\\\n2 & 9 & 8 \\\\\n6 & 5 & 2\n\\end{pmatrix} = \n\\begin{pmatrix}\n1 & 0 & 0\\\\\n2 & 1 & 0\\\\\n6 & 1 & 1\n\\end{pmatrix}\n\\begin{pmatrix}\n1 & -1 & 4\\\\\n0 & 11 & 0\\\\\n0 & 0 & -22\n\\end{pmatrix}"
Hence, the inverse of the matrix is "A = U^{-1} L^{-1}".
Since U and L are already in upper and lower triangular form, it is easy to find their inverses using Gauss-Jordan elimination.
Inverse of L:
"\\left(\\begin{array}{ccc|ccc} \n 1 & 0 & 0 & 1 & 0 & 0\\\\ \n 2 & 1 & 0 & 0 & 1 & 0\\\\\n6 & 1 & 1 & 0 & 0 & 1\n\\end{array}\\right) \\sim (R_2 \\rightarrow R_2- 2 R_1; R_3 \\rightarrow R_3- 6 R_1) \\sim"
"\\left(\\begin{array}{ccc|ccc} \n 1 & 0 & 0 & 1 & 0 & 0\\\\ \n 0 & 1 & 0 & -2 & 1 & 0\\\\\n 0 & 1 & 1 & -6 & 0 & 1\n\\end{array}\\right) \\sim(R_3 \\rightarrow R_3 - R_2) \\sim\n\\left(\\begin{array}{ccc|ccc} \n 1 & 0 & 0 & 1 & 0 & 0\\\\ \n 0 & 1 & 0 & -2 & 1 & 0\\\\\n 0 & 0 & 1 & -4 & -1 & 1\n\\end{array}\\right)"
Inverse of U:
"\\left(\\begin{array}{ccc|ccc} \n 1 & -1 & 4 & 1 & 0 & 0\\\\ \n 0 & 11 & 0 & 0 & 1 & 0\\\\\n 0 & 1 & -22 & 0 & 0 & 1\n\\end{array}\\right) \\sim (R_2 \\rightarrow \\frac{R_2}{11}; R_3 \\rightarrow \\frac{R_3}{22}) \\sim\n\\left(\\begin{array}{ccc|ccc} \n 1 & -1 & 4 & 1 & 0 & 0\\\\ \n 0 & 1 & 0 & 0 & \\frac{1}{11} & 0\\\\\n 0 & 0 & 1 & 0 & 0 & -\\frac{1}{22}\n\\end{array}\\right) \\sim (R_1 \\rightarrow R_1 + R_2 - 4R_3) \\sim\n\\left(\\begin{array}{ccc|ccc} \n 1 & 0 & 0 & 1 & \\frac{1}{11} & \\frac{2}{11}\\\\ \n 0 & 1 & 0 & 0 & \\frac{1}{11} & 0\\\\\n 0 & 0 & 1 & 0 & 0 & -\\frac{1}{22}\n\\end{array}\\right)"
Hence, "A^{-1} = U^{-1}L^{-1} = \n\\begin{pmatrix}\n1 & \\frac{1}{11} & \\frac{2}{11}\\\\\n0 & \\frac{1}{11} & 0\\\\\n0 & 0 & -\\frac{1}{22}\n\\end{pmatrix}\n\\begin{pmatrix}\n1 & 0 & 0\\\\\n-2 & 1 & 0\\\\\n-4 & -1 & 1\n\\end{pmatrix} = \n\\begin{pmatrix}\n\\frac{1}{11} & -\\frac{1}{11} & \\frac{2}{11}\\\\\n-\\frac{2}{11} & \\frac{1}{11} & 0 \\\\\n\\frac{2}{11} & \\frac{1}{22} & -\\frac{1}{22}\n\\end{pmatrix}".
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