Find a kernel and image basis of a linear transformation

In summary, to find the kernel basis for a linear transformation, we can set up a system of equations using the associated matrix and solve for the coordinates of the vectors in a given basis. Then, by taking linear combinations, we can find the actual vectors that form the basis for the kernel.
  • #1
Hernaner28
263
0

Homework Statement



Find a kernel and image basis of the linear transformation having:

[tex] \displaystyle T:{{\mathbb{R}}^{3}}\to {{\mathbb{R}}^{3}}[/tex] so that

[tex] \displaystyle _{B}{{\left( T \right)}_{B}}=\left( \begin{matrix}
1 & 2 & 1 \\
2 & 4 & 2 \\
0 & 0 & 0 \\
\end{matrix} \right)[/tex]

[tex] \displaystyle B=\left\{ \left( 1,1,0 \right),\left( 0,2,0 \right),\left( 2,0,-1 \right) \right\}[/tex]

Homework Equations

The Attempt at a Solution



For the image basis it is easy given the fact that the rank of the associated matrix is 1 so, the image is generated by one column.

The problem comes when finding the Kernel basis. My idea is to save the general fromula of the linear map which would work for sure but I wanted to know if there's a quicker way of doing it without finding the general formula of the linear map.Thanks!
 
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  • #2
To find the kernel, you'll need to find the (x,y,z) such that

[tex]\left(\begin{array}{ccc} 1 & 2 & 1\\ 2 & 4 & 2\\ 0 & 0 & 0\end{array}\right)\left(\begin{array}{c} x\\ y\\ z\\\end{array}\right)=\left(\begin{array}{c} 0\\ 0\\ 0\\\end{array}\right)[/tex]

This is a system of equations whose solution is not that hard to find.

(note: you know the rank of the matrix, so the dimension of the kernel is easy to find out)
 
  • #3
Yeah, the dimension of the kernel should be 2. I also thought about that system, but I've got some doubts with it.

We have:

$$\left(\begin{array}{ccc} 1 & 2 & 1\\ 2 & 4 & 2\\ 0 & 0 & 0\end{array}\right)\left(\begin{array}{c} x\\ y\\ z\\\end{array}\right)=\left(\begin{array}{c} 0\\ 0\\ 0\\\end{array}\right)$$

But there, what is (x,y,z)? Are they coordinates or is it a vector? What I understand is that if I multiply the associated matrix with the COORDINATES of a vector in base B then the result is the coordinates of the vector TRANSFORMATION. Is that right?

Thanks!
 
  • #4
The (x,y,z) are coordinates of a vector with respect to base B. If you want to find the corresponding vector, this can easily be done.
 
  • #5
Ahhm, I see. So we get that:

[tex]Ker\left( T \right) = \left\{ {\left( {x,y, - x - 2y} \right)} \right\}[/tex]

Right? So there we have the set of the coordinates of the vectors in basis B whose transformation is 0. Or are they vectors?

Thanks
 
  • #6
Hernaner28 said:
Ahhm, I see. So we get that:

[tex]Ker\left( T \right) = \left\{ {\left( {x,y, - x - 2y} \right)} \right\}[/tex]

Right? So there we have the set of the coordinates of the vectors in basis B whose transformation is 0. Or are they vectors?

Thanks

They are coordinates for vectors. You can first take special values for x and y to find two special coordinates in the kernel. Then you have to find the corresponding vector.
 
  • #7
Alright so, we have the set of the coordinates of the vectors whose images are the null vector.
To find the generator of the coordinates:

[tex]\left( {x,y, - x - 2y} \right) = x\left( {1, - 1,0} \right) + y\left( {0,1, - 2} \right)[/tex]

So: [tex]\left\{ {\left( {1, - 1,0} \right),\left( {0,1, - 2} \right)} \right\}[/tex] is a generator (basis) of the coordinates. Now, how can I get the basis of the actual vectors but not in base B?Thanks!
 
  • #8
Do you know what coordinates are?? How are they defined??
 
  • #9
Yes, they are the coefficients of the linear combination of the base. I got that

$$\left\{ {\left( {1, - 1,0} \right),\left( {0,1, - 2} \right)} \right\}$$

is a basis of the kernel. But those elements are vectors or what?
 
  • #10
Ok, so take the linear combination.

For example, the coordinates (1,2,3) would correspond to the vector

[tex](1,1,0)+2(0,2,0)+3(2,0,-1)[/tex]
 
  • #11
Ahhh I get it now by that way! So:

[tex]x\left( {1,1,0} \right) + y\left( {0,2,0} \right) + \left( { - x - 2y} \right)\left( {2,0, - 1} \right) = \left( { - x - 4y,x + 2y,x + 2y} \right)[/tex]

And:

[tex]\left( { - x - 4y,x + 2y,x + 2y} \right) = x\left( { - 1,1,1} \right) + y\left( { - 4,2,2} \right)[/tex]

So a basis of the kernel is:
[tex]{\left( { - 1,1,1} \right),\left( { - 4,2,2} \right)}[/tex]

Now just a last question. What was wrong about:

$$\left( {x,y, - x - 2y} \right) = x\left( {1, - 1,0} \right) + y\left( {0,1, - 2} \right)$$

How could I solve the problem following that way? It would be the same, wouldn't it?Thanks!
 
  • #12
Hernaner28 said:
Now just a last question. What was wrong about:

$$\left( {x,y, - x - 2y} \right) = x\left( {1, - 1,0} \right) + y\left( {0,1, - 2} \right)$$

How could I solve the problem following that way?

Nothing was wrong about that. It just gives you coordinates of a vector. That is, (1,-1,0) and (0,1,-2) are coordinates of a certain vector. Take linear combinations to find the actual vector.
 
  • #13
Thank you very much for your efficiency and quickness for helping (the best combination) :)
 

Related to Find a kernel and image basis of a linear transformation

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another, while preserving the properties of vector addition and scalar multiplication. In simpler terms, it is a function that takes in a set of vectors and outputs another set of vectors.

2. What is a kernel in linear algebra?

In linear algebra, the kernel of a linear transformation is the set of all vectors that get mapped to the zero vector in the output space. In other words, it is the set of all vectors that the transformation "kills" or maps to the origin.

3. How do you find the kernel of a linear transformation?

To find the kernel of a linear transformation, you can set up a system of equations and solve for the variables that result in a zero vector output. Alternatively, you can use matrix operations to reduce the transformation to its row-echelon form and find the free variables that correspond to the kernel.

4. What is an image basis in linear algebra?

In linear algebra, the image basis of a linear transformation is the set of vectors that span the range or output space of the transformation. In other words, it is the set of all possible outputs that can be generated by the transformation.

5. How do you find the image basis of a linear transformation?

To find the image basis of a linear transformation, you can use matrix operations to reduce the transformation to its row-echelon form and identify the pivot columns. The vectors corresponding to these pivot columns will form the image basis.

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