Difference between revisions of "Image (mathematics)"
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If the rows (or columns, equivalently) of a matrix ''A'' are [[Linear independence|linearly independent]], then the image of that transformation is the entire space it is applied to. | If the rows (or columns, equivalently) of a matrix ''A'' are [[Linear independence|linearly independent]], then the image of that transformation is the entire space it is applied to. | ||
| + | |||
| + | ==Examples== | ||
| + | |||
| + | ===Example 1=== | ||
| + | |||
| + | Consider all the points (vectors) in the plane, ie, ''(x,y)'' acting under the transformation | ||
| + | |||
| + | <math>\mathbf{A} = \begin{pmatrix} | ||
| + | |||
| + | -1 & 1 \\ | ||
| + | 1 & 0 \end{pmatrix}</math>. | ||
| + | |||
| + | We can be sure that the image of this transformation is the entire plane, because for any point | ||
| + | |||
| + | <math>\begin{pmatrix} | ||
| + | |||
| + | x \\ | ||
| + | y \end{pmatrix}</math> | ||
| + | |||
| + | in the plane, there is another vector in the plane | ||
| + | |||
| + | <math>\begin{pmatrix} | ||
| + | |||
| + | y \\ | ||
| + | x+y \end{pmatrix}</math> | ||
| + | |||
| + | such that | ||
| + | |||
| + | <math>\begin{pmatrix} -1 & 1 \\ 1 & 0 \end{pmatrix} \begin{pmatrix}y \\x+y \end{pmatrix} = \begin{pmatrix}x \\y \end{pmatrix}</math>. | ||
| + | |||
| + | ===Example 2=== | ||
| + | |||
| + | We continue to work in the plane, but now we examine the matrix | ||
| + | |||
| + | <math>\mathbf{A} = \begin{pmatrix} | ||
| + | |||
| + | 3 & 1 \\ | ||
| + | -6 & -2 \end{pmatrix}</math>. | ||
| + | |||
| + | Now if we examine how this matrix acts on an arbitary point ''(a,b)'', we find that point is carried to | ||
| + | |||
| + | <math>\mathbf{A} = \begin{pmatrix}3 & 1 \\-6 & -2 \end{pmatrix}\begin{pmatrix}a \\b \end{pmatrix} = \begin{pmatrix}3a+b \\-6a-2b \end{pmatrix} = \begin{pmatrix}1 \\-3 \end{pmatrix}(a+b)</math>, | ||
| + | |||
| + | in other words, all points in the plane are carried to the line <math>y=-3x \ </math>. | ||
| + | |||
| + | We write | ||
| + | |||
| + | <math>im(\mathbf{A}) = \begin{pmatrix}1 \\-3 \end{pmatrix}t, \forall t\in\mathbb{R} \ </math>. | ||
| + | |||
| + | |||
[[Category:linear algebra]] | [[Category:linear algebra]] | ||
[[Category:mathematics]] | [[Category:mathematics]] | ||
Revision as of 22:12, February 28, 2010
In mathematics, the image of a linear transformation is its range: all possible values generated by the transformation. A matrix A, which is an expression of a function, has an image denoted by im(A).
If the rows (or columns, equivalently) of a matrix A are linearly independent, then the image of that transformation is the entire space it is applied to.
Examples
Example 1
Consider all the points (vectors) in the plane, ie, (x,y) acting under the transformation
.
We can be sure that the image of this transformation is the entire plane, because for any point
in the plane, there is another vector in the plane
such that
.
Example 2
We continue to work in the plane, but now we examine the matrix
.
Now if we examine how this matrix acts on an arbitary point (a,b), we find that point is carried to
,
in other words, all points in the plane are carried to the line .
We write
.