Please help. What is the relation between the kernel of A an

This means that the kernel of A^2+ A is the same as the kernel of (A+ I)A. By the definition of the kernel, this means that any vector x that is in the kernel of (A+ I)A is also in the kernel of A^2+ A. Therefore, the kernel of (A+ I)A is a subset of the kernel of A^2+ A.
  • #1
Candice
2
0

Homework Statement


  1. What is the relation between the kernel of A and the kernel of (A^2 + A)?

Homework Equations

The Attempt at a Solution



Break into A^2x = 0 and Ax = 0. We know Ax = 0 because that's the kernel of A, ker(A^2x) is subset of ker(A) so ker(A^2 + A) is a subset of ker (A)?
 
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  • #2
Candice said:

Homework Statement


  1. What is the relation between the kernel of A and the kernel of (A^2 + A)?

Homework Equations

The Attempt at a Solution



Break into A^2x = 0 and Ax = 0. We know Ax = 0 because that's the kernel of A, ker(A^2x) is subset of ker(A) so ker(A^2 + A) is a subset of ker (A)?

Why not start with ##x \in ker(A)## and start from there? You need to formalise your answer. You've got an outline for the answer, but you need to sharpen your logic.
 
Last edited:
  • #3
In both this and the previous question about image, it is useful to note that [itex]A^2+ A= A(A+ I)= (A+ I)A[/itex].
 

FAQ: Please help. What is the relation between the kernel of A an

1. What is the kernel of matrix A?

The kernel of a matrix A is the set of all vectors that when multiplied by A result in the zero vector. In other words, it is the solution space to the homogeneous equation Ax=0.

2. How is the kernel of A related to the original matrix A?

The kernel of A is closely related to the original matrix A as it represents the set of vectors that are mapped to the zero vector by A. In other words, the kernel is a subset of the domain of A.

3. What does the kernel of A tell us about the linear transformation represented by A?

The kernel of A provides information about the nullity of A, which is the dimension of the kernel. This tells us how many linearly independent vectors are mapped to the zero vector by A, and can provide insight into the invertibility and rank of A.

4. How can we find the kernel of A?

To find the kernel of A, we can solve the homogeneous equation Ax=0 using techniques such as Gaussian elimination or matrix row operations. The resulting solutions will form the basis for the kernel.

5. Can the kernel of A be empty?

Yes, it is possible for the kernel of A to be empty. This would occur when there are no vectors that are mapped to the zero vector by A, meaning the nullity of A is zero. In this case, the matrix A would be one-to-one and have a full rank.

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