Linear algebra - kernel and image question

Click For Summary

Homework Help Overview

The discussion revolves around a linear transformation f from K³ to K⁴, where K³ and K⁴ are vector spaces defined by their respective bases. Participants are tasked with determining a matrix representation of the transformation and identifying the kernel and image of f.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants explore the representation of vector spaces as matrices and question the dimensionality of the transformation matrix. There are attempts to clarify the notation used for the linear transformation and the bases of the vector spaces. Some participants express uncertainty about the correctness of the matrix representation and the implications of the dimensions involved.

Discussion Status

There is ongoing clarification regarding the relationship between the dimensions of the vector spaces and the transformation matrix. Some participants have provided insights into the kernel and image of the transformation, while others are still grappling with the notation and assumptions made in the problem setup.

Contextual Notes

Participants note that the actual vectors used in the transformation are assumed rather than given, and there is discussion about the implications of the dimensions of the matrix in relation to the vector spaces involved.

iloveannaw
Messages
38
Reaction score
0

Homework Statement



f: K^{3} \rightarrow K^{4} is a linear transformation of vector spaces:

K^{3} = \left\langle \vec{e}_{1}, \vec{e}_{2}, \vec{e}_{3} \right\rangle

and

K^{4} = \left\langle \vec{e}^{*}_{1}, \vec{e}^{*}_{2}, \vec{e}^{*}_{3}, \vec{e}^{*}_{4} \right \rangle

as well as:

f(\vec{e}_{1}) = \vec{e}^{*}_{1} - \vec{e}^{*}_{2} + \vec{e}^{*}_{3} - \vec{e}^{*}_{4},

f(\vec{e}_{2}) = \vec{e}^{*}_{1} - 2 \vec{e}^{*}_{3},

f(\vec{e}_{1}) = \vec{e}^{*}_{2} - 3 \vec{e}^{*}_{3} + \vec{e}^{*}_{4}.

Determine a matrix A so that for all x \in K^{3} so that

f(x) = Ax
Determine the kernel and image of f.


Homework Equations



The Attempt at a Solution



well I assumed the following:

K^{3} = \left\langle \vec{e}_{1} \vec{e}_{2} \vec{e}_{3} \right\rangle \[<br /> =<br /> \left[ {\begin{array}{ccc}<br /> 1 &amp; 0 &amp; 0 \\<br /> 0 &amp; 1 &amp; 0 \\<br /> 0 &amp; 0 &amp; 1 \\<br /> \end{array} } \right]<br /> \]<br />

K^{4} = \left\langle \vec{e}^{*}_{1} \vec{e}^{*}_{2} \vec{e}^{*}_{3} \vec{e}^{*}_{4} \right \rangle \[&lt;br /&gt; =&lt;br /&gt; \left[ {\begin{array}{cccc}&lt;br /&gt; 1 &amp;amp; 0 &amp;amp; 0 &amp;amp; 0 \\&lt;br /&gt; 0 &amp;amp; 1 &amp;amp; 0 &amp;amp; 0 \\&lt;br /&gt; 0 &amp;amp; 0 &amp;amp; 1 &amp;amp; 0 \\&lt;br /&gt; 0 &amp;amp; 0 &amp;amp; 0 &amp;amp; 1 \\&lt;br /&gt; \end{array} } \right]&lt;br /&gt; \]&lt;br /&gt;<br /> f(\vec{e}_{1}) \[&lt;br /&gt; =&lt;br /&gt; \left[ {\begin{array}{c}&lt;br /&gt; 1 \\&lt;br /&gt; -1 \\&lt;br /&gt; 1 \\&lt;br /&gt; -1 \\&lt;br /&gt; \end{array} } \right]&lt;br /&gt; \]&lt;br /&gt;,<br /> <br /> f(\vec{e}_{2}) \[&lt;br /&gt; =&lt;br /&gt; \left[ {\begin{array}{c}&lt;br /&gt; 1 \\&lt;br /&gt; 0 \\&lt;br /&gt; -2 \\&lt;br /&gt; 0 \\&lt;br /&gt; \end{array} } \right]&lt;br /&gt; \]&lt;br /&gt;,<br /> <br /> f(\vec{e}_{1}) \[&lt;br /&gt; =&lt;br /&gt; \left[ {\begin{array}{c}&lt;br /&gt; 0 \\&lt;br /&gt; 1 \\&lt;br /&gt; -3 \\&lt;br /&gt; 1 \\&lt;br /&gt; \end{array} } \right]&lt;br /&gt; \]&lt;br /&gt;.<br /> <br /> f(x) \[&lt;br /&gt; =&lt;br /&gt; \left[ {\begin{array}{ccc}&lt;br /&gt; 1 &amp;amp; 1 &amp;amp; 0 \\&lt;br /&gt; -1 &amp;amp; 0 &amp;amp; 1 \\&lt;br /&gt; 1 &amp;amp; 2 &amp;amp; -3 \\&lt;br /&gt; -1 &amp;amp; 0 &amp;amp; 1 \\&lt;br /&gt; \end{array} } \right]&lt;br /&gt; \]&lt;br /&gt; \[&lt;br /&gt; = Ax = A&lt;br /&gt; \left[ {\begin{array}{ccc}&lt;br /&gt; 1 &amp;amp; 0 &amp;amp; 0 \\&lt;br /&gt; 0 &amp;amp; 1 &amp;amp; 0 \\&lt;br /&gt; 0 &amp;amp; 0 &amp;amp; 1 \\&lt;br /&gt; \end{array} } \right]&lt;br /&gt; \]&lt;br /&gt; = A = \[&lt;br /&gt; \left[ {\begin{array}{ccc}&lt;br /&gt; 1 &amp;amp; 1 &amp;amp; 0 \\&lt;br /&gt; -1 &amp;amp; 0 &amp;amp; 1 \\&lt;br /&gt; 1 &amp;amp; 2 &amp;amp; -3 \\&lt;br /&gt; -1 &amp;amp; 0 &amp;amp; 1 \\&lt;br /&gt; \end{array} } \right]&lt;br /&gt; \]&lt;br /&gt;<br /> <br /> so that&#039;s A, but I don&#039;t think it can be right for a start its not 4D.<br /> I know how to get the kernel and image but I don&#039;t really know how else to start this problem
 
Last edited:
Physics news on Phys.org
so there are 2 questions in fact?
 
iloveannaw said:

The Attempt at a Solution



well I assumed the following:

K^{3} = \left\langle \vec{e}_{1} \vec{e}_{2} \vec{e}_{3} \right\rangle \[<br /> =<br /> \left[ {\begin{array}{ccc}<br /> 1 &amp; 0 &amp; 0 \\<br /> 0 &amp; 1 &amp; 0 \\<br /> 0 &amp; 0 &amp; 1 \\<br /> \end{array} } \right]<br /> \]<br />

K^{4} = \left\langle \vec{e}^{*}_{1} \vec{e}^{*}_{2} \vec{e}^{*}_{3} \vec{e}^{*}_{4} \right \rangle \[<br /> =<br /> \left[ {\begin{array}{cccc}<br /> 1 &amp; 0 &amp; 0 &amp; 0 \\<br /> 0 &amp; 1 &amp; 0 &amp; 0 \\<br /> 0 &amp; 0 &amp; 1 &amp; 0 \\<br /> 0 &amp; 0 &amp; 0 &amp; 1 \\<br /> \end{array} } \right]<br /> \]<br />
What is that supposed to mean? K3 and K4 are matrices?
f(x) \[<br /> =<br /> \left[ {\begin{array}{ccc}<br /> 1 &amp; 1 &amp; 0 \\<br /> -1 &amp; 0 &amp; 1 \\<br /> 1 &amp; 2 &amp; -3 \\<br /> -1 &amp; 0 &amp; 1 \\<br /> \end{array} } \right]<br /> \]<br /> \[<br /> = Ax = A<br /> \left[ {\begin{array}{ccc}<br /> 1 &amp; 0 &amp; 0 \\<br /> 0 &amp; 1 &amp; 0 \\<br /> 0 &amp; 0 &amp; 1 \\<br /> \end{array} } \right]<br /> \]<br /> = A = \[<br /> \left[ {\begin{array}{ccc}<br /> 1 &amp; 1 &amp; 0 \\<br /> -1 &amp; 0 &amp; 1 \\<br /> 1 &amp; 2 &amp; -3 \\<br /> -1 &amp; 0 &amp; 1 \\<br /> \end{array} } \right]<br /> \]<br />
You seriously need to clean up your notation. What you wrote doesn't make much sense.
so that's A, but I don't think it can be right for a start its not 4D.
I know how to get the kernel and image but I don't really know how else to start this problem
Your matrix A is correct (except for a typo in the second column). It's 4x3, so it represents a map from a three-dimensional vector space to a four-dimensional vector space.
 
Last edited:
What is that supposed to mean? K3 and K4 are matrices?

K3 and k4 are vector spaces with bases:

K^{3} = \left\langle \vec{e}_{1} , \vec{e}_{2} , \vec{e}_{3} \right\rangle

K^{4} = \left\langle \vec{e}^{*}_{1} , \vec{e}^{*}_{2} , \vec{e}^{*}_{3} , \vec{e}^{*}_{4} \right \rangle

the elements within a basis are indeed vectors, therefore K3 and k4 can be represented as matrices. However, as i said the actual vectors I've chosen are assumed not given!

\vec{e}_{i} is usually taken to be a unit vector in i-th dimension.

You seriously need to clean up your notation. What you wrote doesn't make much sense.

sorry, Latex is not fun. let me try again:

f(x) = Ax , where
<br /> \[<br /> f(x) =<br /> \left( {\begin{array}{c}<br /> \vec{e}_{1} \\<br /> \vec{e}_{2} \\<br /> \vec{e}_{3} \\<br /> \end{array} } \right)<br /> \]

and
<br /> \[<br /> x =<br /> \begin{array}{ccc}<br /> 1 &amp; 0 &amp; 0\\<br /> 0 &amp; 1 &amp; 0\\<br /> 0 &amp; 0 &amp; 1\\<br /> \end{array}<br /> \]<br />
therefore:

<br /> \[<br /> A =<br /> \left[ {\begin{array}{ccc}<br /> 1 &amp; 1 &amp; 0 \\<br /> -1 &amp; 0 &amp; 1 \\<br /> 1 &amp; -2 &amp; -3 \\<br /> -1 &amp; 0 &amp; 1 \\<br /> \end{array} } \right]<br /> \]<br />

but i thought the dimension of a matrix was linked to the no. of pivots in this case the maximum is three.

thanks!
 
Last edited:
iloveannaw said:
K3 and k4 are vector spaces with bases:

K^{3} = \left\langle \vec{e}_{1} , \vec{e}_{2} , \vec{e}_{3} \right\rangle

K^{4} = \left\langle \vec{e}^{*}_{1} , \vec{e}^{*}_{2} , \vec{e}^{*}_{3} , \vec{e}^{*}_{4} \right \rangle

the elements within a basis are indeed vectors, therefore K3 and k4 can be represented as matrices.
No, they cannot. Linear transformations from one vectors space to another are represented by matrices, or individual vectors (such as the basis vectors) as column matrices, not the vector spaces themselves.

However, as i said the actual vectors I've chosen are assumed not given!

\vec{e}_{i} is usually taken to be a unit vector in i-th dimension.



sorry, Latex is not fun. let me try again:

f(x) = Ax , where
<br /> \[<br /> f(x) =<br /> \left( {\begin{array}{c}<br /> \vec{e}_{1} \\<br /> \vec{e}_{2} \\<br /> \vec{e}_{3} \\<br /> \end{array} } \right)<br /> \]

and
<br /> \[<br /> x =<br /> \begin{array}{ccc}<br /> 1 &amp; 0 &amp; 0\\<br /> 0 &amp; 1 &amp; 0\\<br /> 0 &amp; 0 &amp; 1\\<br /> \end{array}<br /> \]<br />
therefore:

<br /> \[<br /> A =<br /> \left[ {\begin{array}{ccc}<br /> 1 &amp; 1 &amp; 0 \\<br /> -1 &amp; 0 &amp; 1 \\<br /> 1 &amp; -2 &amp; -3 \\<br /> -1 &amp; 0 &amp; 1 \\<br /> \end{array} } \right]<br /> \]<br />

but i thought the dimension of a matrix was linked to the no. of pivots in this case the maximum is three.

thanks!
What you have is a perfectly good matrix representing a linear transformation from a 3 dimensional space (it has 3 columns) to a 4 dimensional space (it has 4 rows).
The kernel is the subspace of K3 of vectors v such that Av= 0. That specifically means that they are of the form (x, y, z) such that x+ y= 0, -x+ z= 0, x- 2y- 3z= 0, and -x+ z= 0. Notice that the second and fourth equations are the same and both say z= x. Putting that into the first and third equations, gives you another equation for x and y so you can solve for y as a linear function of x and write any vector in the kernel as a multiple of x.

The image of f is the set of all vectors in K4 that are equal to f(v) for some v in K3. That is, (a, b, c, d) such that x+ y= a, -x+ z= b, x- 2y- 3z= c, and -x+ z= d have solutions. Again, the second and fourth equation both have "-x+ z" so we must have b= d. Putting z= b+ x into the third equation gives equations you can use to get conditions on b and c. Since the kernel is one dimensional and K3 is three dimensional, the image must have dimension 3- 1= 2.
 
No, they cannot. Linear transformations from one vectors space to another are represented by matrices, or individual vectors (such as the basis vectors) as column matrices, not the vector spaces themselves.

thanks for clearing that up :)

What you have is a perfectly good matrix representing a linear transformation from a 3 dimensional space (it has 3 columns) to a 4 dimensional space (it has 4 rows).

ok, so the four dimensions of K4 refer only to the space and our matrix A does not necessarily have the same number of dimensions as the resulting vector space ? thanks again
 

Similar threads

  • · Replies 5 ·
Replies
5
Views
2K
Replies
1
Views
1K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
19
Views
1K
  • · Replies 4 ·
Replies
4
Views
1K
Replies
6
Views
1K
  • · Replies 9 ·
Replies
9
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K