Linear Algebra- Kernel and images of a matrix

In summary: If x \in \ker(A), then for any x, A^2x is also in \operatorname{im}(A^2). This means that \operatorname{im}(A^2) contains x, but is not necessarily equal to it because it could also contain another vector.
  • #1
KyleS4562
18
0

Homework Statement



Consider a square matrix A:

a. What is the relationship between ker(A) and ker(A^2)? Are they necessarily equal? Is one of them necessarily contained in the other? More generally, What can you say about ker(A), ker(A^2), ker(A^3), ker(A^4),...?

b. What can you say about im(A), im(A^2), im(A^3), im(A^4),...?


2. The attempt at a solution

So i believe if A is invertible nxn matrix, than ker(A)={<0,0,0>} and so will ker(A^2) and so on. And the image of A if A is invertible is im(A)=R^n and so will the im(A^2) and so on, but I am not sure what it would be for other conditions of A at least that's what I think this question wants.
 
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  • #2
a. If [tex]x \in \ker(A)[/tex], what can you say about [tex]A^2 x[/tex]? What does that tell you about [tex]\ker(A^2)[/tex]?

b. For any [tex]x[/tex], [tex]A^2x[/tex] is in [tex]\operatorname{im}(A^2)[/tex]. If you rewrite [tex]A^2x[/tex] as [tex]A(Ax)=Ay[/tex], what can you say about [tex]\operatorname{im}(A)[/tex]?
 
  • #3
for A: A^2 * x would equal the zero vector which means the ker(A^2) contains x but is not necessarily equal because it may contain another vector

B. Is that saying the im(A) contains the im(A^2) but is not necessarily equal to the im(A^2) because it will span more vectors?
 
  • #4
KyleS4562 said:
for A: A^2 * x would equal the zero vector which means the ker(A^2) contains x but is not necessarily equal because it may contain another vector

In other words, we have [tex]\ker(A)\subset \ker(A^2)[/tex].

KyleS4562 said:
B. Is that saying the im(A) contains the im(A^2) but is not necessarily equal to the im(A^2) because it will span more vectors?

Yes. You could also write : [tex]\operatorname{im}(A^2)\subset \operatorname{im}(A)[/tex]

Now, how can you apply this to [tex]\ker(A^3)[/tex], [tex]\ker(A^4)[/tex]... and [tex]\operatorname{im}(A^3)[/tex], [tex]\operatorname{im}(A^4)[/tex]...?
 
  • #5
alright, thank you very much for your help
 

Related to Linear Algebra- Kernel and images of a matrix

1. What is the definition of a kernel in linear algebra?

The kernel of a matrix is the set of all vectors that, when multiplied by the matrix, result in a zero vector. In other words, it is the set of all inputs that produce a zero output when operated on by the matrix.

2. How is the kernel related to the concept of linear independence?

A set of vectors is linearly independent if and only if the only solution to the equation Ax=0 is the trivial solution, where A is a matrix and x is a vector. Therefore, the kernel of a matrix can be seen as the set of all linearly independent vectors that produce a zero output when operated on by the matrix.

3. Can the kernel of a matrix be empty?

Yes, it is possible for a matrix to have an empty kernel. This occurs when the only solution to the equation Ax=0 is the trivial solution, meaning all the vectors in the matrix are linearly independent.

4. How is the image of a matrix different from the kernel?

The image of a matrix is the set of all possible outputs that can be produced by operating on the matrix with different input vectors. It is a subset of the vector space that the matrix operates on. In contrast, the kernel is a set of input vectors that produce a zero output, and is a subset of the domain of the matrix.

5. How can the kernel and image of a matrix be used in real-world applications?

The kernel and image of a matrix are important concepts in linear algebra that have many real-world applications. For example, in data analysis, the kernel of a matrix is used to find patterns and relationships in a dataset, while the image of a matrix is used to identify important features or variables. In computer graphics, the kernel of a transformation matrix can be used to identify the center of rotation or scaling, while the image can be used to determine the resulting shape or size of an object. These are just a few examples of how the kernel and image of a matrix can be applied in various fields.

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