Bases of a Linear transformation (Kernel, Image and Union ?

In summary, the conversation discussed the bases of a linear transformation, specifically the kernel, image, and union. The basis for the kernel was found by row reducing a matrix and resulted in two vectors. The basis for the image was found by writing the transformation as a matrix and row reducing it, resulting in two linearly independent vectors. The process for finding the basis for the union was also mentioned.
  • #1
sid9221
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Bases of a Linear transformation (Kernel, Image and Union ?

http://dl.dropbox.com/u/33103477/1linear%20tran.png

For the kernel/null space
[tex] \begin{bmatrix}
3 & 1 & 2 & -1\\
2 & 4 & 1 & -1
\end{bmatrix} = [0]_v [/tex]

Row reducing I get

[tex] \begin{bmatrix}
1 & 0 & \frac{7}{9} & \frac{-2}{9}\\
0 & 1 & \frac{-1}{10} & \frac{-1}{10}
\end{bmatrix} = [0]_v [/tex]

So the basis of the kernel U1 is:
[tex] \begin{pmatrix}
\frac{-7}{9}\\
\frac{1}{10}\\
1\\
0
\end{pmatrix}, \begin{pmatrix}
\frac{2}{9}\\
\frac{1}{10}\\
0\\
1
\end{pmatrix} [/tex]

Now, for the image/range.

I can write the transformation as:

[tex] S=\begin{pmatrix}
1 \\
1 \\
2 \\
3
\end{pmatrix}, \begin{pmatrix}
-1 \\
-3 \\
-8 \\
-27
\end{pmatrix}
[/tex]

So we proceed to find the basis of Span S

[tex] \begin{bmatrix}
1 &-1 \\
1 &-3 \\
2 &-8 \\
3 &-27
\end{bmatrix} [/tex]

Row reducing I get:

[tex] \begin{bmatrix}
1 &0 \\
0 &1 \\
0 &0 \\
0 &0
\end{bmatrix} [/tex]

Which implies S is linearly independant.

So the basis is:[tex] S=\begin{pmatrix}
1 \\
1 \\
2 \\
3
\end{pmatrix}, \begin{pmatrix}
-1 \\
-3 \\
-8 \\
-27
\end{pmatrix}
[/tex]

Now for U1 union U2

Should I just put both the basis together. (After checking if they are all independant ?)

I have no idea about the addition any ideas ??
 
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  • #2


Any one ?
 

Related to Bases of a Linear transformation (Kernel, Image and Union ?

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another in a way that preserves the structure of the original space. This means that the transformation preserves operations such as addition and scalar multiplication.

2. What is the kernel of a linear transformation?

The kernel of a linear transformation is the set of all vectors in the domain that get mapped to the zero vector in the codomain. In other words, it is the set of all inputs that result in an output of zero.

3. What is the image of a linear transformation?

The image of a linear transformation is the set of all possible outputs that are generated by applying the transformation to the entire domain. In other words, it is the set of all possible outputs that can be obtained from the transformation.

4. What is the union of a linear transformation?

The union of a linear transformation refers to the combination of the kernel and the image. It includes all the vectors in the domain that get mapped to the zero vector, as well as all the possible outputs that can be obtained from the transformation.

5. How are the kernel, image, and union related in a linear transformation?

The kernel, image, and union are all important concepts in understanding the properties of a linear transformation. The kernel and image are complementary sets, with the kernel containing the inputs that result in the zero vector and the image containing the outputs that can be obtained. The union is the combination of these two sets, representing all the possible inputs and outputs of the transformation.

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