1. Find the vector form of the general solution of the given linear system Ax = b ; then use that result to find the vector form of the general solution of Ax = 0.
"\\begin{cases}\n x_1+x_2+2x_3=6\n\\\\x_1+x_3=-2\n\\\\ 2x_1+x_2+3x_3=4\n\\end{cases}"
Let "x_3=t" , replace this in the second equation: "x_1=-2-t"
Then replace "x_3=t, x_1=-2-t" in the first and third equations:
"\\begin{cases}\n (-2-t)+x_2+2t=6\n\n\\\\ 2(-2-t)+x_2+3t=4\n\\end{cases}, \\quad \n x_2= 8-t"
The general solution of the linear system Ax=b is
"\\begin{bmatrix}\nx_1\n\\\\ x_2\n\\\\ x_3\n\\end{bmatrix} = \n\\begin{bmatrix}\n-2-t\n\\\\ 8-t\n\\\\t\n\\end{bmatrix}\n= \\begin{bmatrix}\n-2 \\\\ 8 \\\\0 \\end{bmatrix}+ t\\begin{bmatrix}-1 \\\\ -1 \\\\ 0\\end{bmatrix}, \\quad t\\in \\mathbb{R}"
The general solution of the linear system Ax=0 is
"\\begin{bmatrix}\nx_1\n\\\\ x_2\n\\\\ x_3\n\\end{bmatrix} = \n\n t\\begin{bmatrix}-1 \\\\ -1 \\\\ 0\\end{bmatrix}, \\quad t\\in \\mathbb{R}"
2. Find a basis for the null space and row space of A.
"A =\\begin{bmatrix} 1&-1&3\n\\\\ 5&-4&-2\n\\\\ 7&-6&4\n\\end{bmatrix}"
We reduce the matrix A as follows
"A =\\begin{bmatrix} 1&-1&3\n\\\\ 5&-4&-2\n\\\\ 7&-6&4\n\\end{bmatrix} \\to ^{R_2-5R_1}_{R_3-7R_1}\\to\n\n\\begin{bmatrix} 1&-1&3\n\\\\ 0&1&-17\n\\\\ 0&1&-17\n\\end{bmatrix} \n\\to^{R_3-R_2}_{R_1+R_2} \\to \n\\begin{bmatrix} 1&0&-14\n\\\\ 0&1&-17\n\\\\ 0&0&0\n\\end{bmatrix}"
The last matrix is in reduced row echelon form.
a) basis for null space
We see that the general solution of Ax=0 is
"\\begin{cases} \nx_1=14x_3\n\\\\ x_2=17x_3\n\\end{cases}"
where "x_3" is free variable.
The vector form solution to Ax=0 is
"\\begin{bmatrix}\nx_1\n\\\\ x_2\n\\\\ x_3\n\\end{bmatrix} = \n\n x_3\\begin{bmatrix}14 \\\\ 17 \\\\ 1\\end{bmatrix}, \\quad x_3\\in \\mathbb{R}"
The null space of the matrix A is given by
"N(A)=\\{ x\\in \\mathbb{R}^3 | x=\n x_3\\begin{bmatrix}14 \\\\ 17 \\\\ 1\\end{bmatrix}, \\quad x_3\\in \\mathbb{R}\\} = Span \\begin{Bmatrix} {\\begin{bmatrix}14 \\\\ 17 \\\\ 1\\end{bmatrix} }\n\\end{Bmatrix}"
We can see, that vector "\\begin{bmatrix}14 \\\\ 17 \\\\ 1\\end{bmatrix}" is a basis for null space.
b) basis for row space
The nonzero rows of matrix (in reduced row echelon form) is a basis for the row space of A.
Thus, "\\begin{Bmatrix}\n\\begin{bmatrix}1 \\\\ 0 \\\\ -14\\end{bmatrix},\\begin{bmatrix}0 \\\\ 1 \\\\ -17\\end{bmatrix}\n\\end{Bmatrix}" is a basis for the row space of A.
3. A matrix in row echelon form is given. By inspection, find bases for the row and column spaces of the matrix A.
"A=\\begin{pmatrix} 1&0&2\n\\\\ 0&0&1\n\\\\ 0&0&0\n\n\\end{pmatrix}"
a) bases for the row space
The nonzero rows of a matrix in row echelon form are linearly independent.
Therefore, the row space has basis "\\begin{Bmatrix}\n\\begin{bmatrix}1 \\\\ 0 \\\\ 2\\end{bmatrix},\\begin{bmatrix}0 \\\\ 0 \\\\ 1\\end{bmatrix}\n\\end{Bmatrix}"
b) bases for the column space
The nonzero columns of a matrix in row echelon form are linearly independent.
Therefore, the column space has basis "\\begin{Bmatrix}\n\\begin{bmatrix}1 \\\\ 0 \\\\ 0\\end{bmatrix},\\begin{bmatrix}2 \\\\ 1 \\\\ 0\\end{bmatrix}\n\\end{Bmatrix}"
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