Let us rewrite the linear system in a matrix form
"\\begin{pmatrix}\n a_{11} & a_{12} & a_{13} \\\\\n a_{21} & a_{22} & a_{23} \\\\\n a_{31} & a_{32} & a_{33} \\\\\n\\end{pmatrix}\n\\cdot \\begin{pmatrix}\n x_1 \\\\\nx_2 \\\\\nx_3\n\\end{pmatrix}\n=\\begin{pmatrix}\n b_1 \\\\\n b_2 \\\\\nb_3\n\\end{pmatrix}" or "\\,\\, A\n\\cdot \\begin{pmatrix}\n x_1 \\\\\nx_2 \\\\\nx_3\n\\end{pmatrix}\n=\\begin{pmatrix}\n b_1 \\\\\n b_2 \\\\\nb_3\n\\end{pmatrix}."
We know that "\\det (A) \\ne 0," so we may write
"\\begin{pmatrix}\n x_1 \\\\\nx_2 \\\\\nx_3\n\\end{pmatrix}\n=A^{-1}\\cdot\\begin{pmatrix}\n b_1 \\\\\n b_2 \\\\\nb_3\n\\end{pmatrix} = \\dfrac{1}{\\det (A)} \\begin{pmatrix}\n A_{11} & A_{21} & A_{31} \\\\\n A_{12} & A_{22} & A_{32} \\\\\n A_{13} & A_{23} & A_{33} \\\\\n\\end{pmatrix}\n\\cdot \\begin{pmatrix}\n b_1 \\\\\n b_2 \\\\\nb_3\n\\end{pmatrix} ."
Here "A_{ij}" are the elements of an adjugate matrix (https://en.wikipedia.org/wiki/Adjugate_matrix). Therefore, according to the rules of matrix multiplication we get
"x_2 = \\dfrac{1}{\\det (A)}\\cdot (A_{12}b_1 + A_{22}b_2 + A_{32}b_3)=\\\\\n=\\dfrac{1}{\\det (A)}\\cdot\\big(-(a_{21}a_{33}-a_{31}a_{23})b_1 + (a_{11}a_{33}-a_{31}a_{13})b_2 - (a_{11}a_{23}-a_{21}a_{13})b_3\\big)." (1)
Now let us compute determinant obtained by replacing the second column of det(A) by (b1; b2; b3)T:
"\\det\\begin{pmatrix}\n a_{11} & b_1 & a_{13} \\\\\n a_{21} & b_2 & a_{23} \\\\\n a_{31} & b_3 & a_{33} \\\\\n\\end{pmatrix}\n= a_{11}(b_2a_{33} - b_3a_{23}) - b_1(a_{21}a_{33}-a_{31}a_{23}) + a_{13}(a_{21}b_3-a_{31}b_2) = \\\\\n= -b_1(a_{21}a_{33}-a_{31}a_{23}) +b_2(a_{11}a_{33}-a_{13}a_{31}) -b_3(a_{11}a_{23}-a_{13}a_{21})."
If we divide the last expression by "\\det (A)" , we'll obtain the expression for "x_2," that we've obtained above (see (1)).
Note that we've obtained a formula from Cramer's rule (see https://en.wikipedia.org/wiki/Cramer's_rule#General_case)
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