Kernels & Images: Matrix A vs. Matrix B

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In summary, the question is whether the kernels and images of a matrix and its reduced row-echelon form are necessarily equal. The answer is yes for the kernel, as it is determined by the augmented matrix and not affected by rref. However, for the image, the answer is no, as rref can change the linearly independent columns and therefore the image.
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Tonyt88
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Homework Statement


Consider a matrix A, and let B = rref(A)
(a) Is ker(A) necessarily equal to ker(B)? Explain.
(b) Is im(A) necessarily equal to im(B)? Explain.


Homework Equations





The Attempt at a Solution


I feel confident saying yes for (a) and no for (b), and what I can articulate is that (a) is true because the kernel is the augmented matrix with the last column with all zeros, thus, it is irrelevant whether or not the matrix is in rref. But I don't know how to express (b).
 
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  • #2
What does rref mean?
 
  • #3
It's reduced row-echelon form, but nevermind, I got the answer, though thanks for the help.
 

Related to Kernels & Images: Matrix A vs. Matrix B

1. What is the difference between a kernel and an image?

A kernel is a matrix that is used to perform a mathematical operation on another matrix, while an image is the output of that operation.

2. How do matrix A and matrix B differ in terms of kernels and images?

Matrix A and matrix B may have different kernel matrices, which means that they will produce different images when operated on.

3. Can two matrices have the same kernel but produce different images?

Yes, two matrices can have the same kernel but produce different images if they have different dimensions or if the values in the matrices are different.

4. What determines the size of the kernel and image?

The size of the kernel and image is determined by the dimensions of the matrices being operated on. The kernel must have the same number of columns as the matrix it is being applied to, and the resulting image will have the same number of rows as the original matrix.

5. Are there any limitations to using kernels and images in matrix operations?

Yes, there are limitations to using kernels and images in matrix operations. The matrices must be compatible in terms of dimensions, and the kernel must be invertible for the operation to be successful.

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