Jordan Normal Form / Jordan basis

In summary, the conversation discusses finding the Jordan Normal form and Jordan basis of a given matrix. The approach involves calculating the characteristic polynomial and eigenvalues, then finding the kernel and using its basis as columns of a new matrix. The lecturer seems to use different methods in different examples, leading to confusion. The main question is whether it matters which columns are taken in the reduced column echelon form.
  • #1
Maybe_Memorie
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Homework Statement



Determine the Jordan Normal form and find some Jordan basis of the matrix
3 -3 1
A = 2 -2 1
2 -3 2

Homework Equations



dim(A) = rk(A) + dimKer(A)

The Attempt at a Solution



My problem here is that my lecturer seems to be doing completely different things with every question and it's getting confusing.

So, I calculated the characteristic polynomial of the matrix, and got one
eigenvalue of t = 1.

So I'm now dealing with the matrix A - tI, in this case A - I.

rk(A - I) = 1, so dimKer(A - I) = 2.

(A - I)^2 = 0 = B

So rk(B) = 0, then dimKer(B) = 3

Continually raising the powers of A - I will results in 0, so the kernels of powers stabilize at the second step, so we should expect a thread of length 2.

The kernel of A - I is spanned by the vectors ( 3/2, 1, 0) and (-1/2, 0, 1)
I should be using columns instead of rows, but I don't know latex so this was the easiest way to write it. Just imagine they were written as columns..


Now, I'm lost. Can you please explain what to do, step by step, and please state where something would be done differently in a different scenario.

Thank you!
 
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  • #2
Here's the main issue, when I find out what vectors span the kernel, and use those as columns of a new matrix, I then reduce that matrix to Reduced Column Echelon Form.

That's fine, but, in some of my lecturers examples he takes a vector corresponding to the missing leading one as a basis, and it others he takes one of the columns of the RCEF.

My question: why the differences and does it matter which of the columns are taken?
 
  • #3
Anyone?
 

What is Jordan Normal Form?

Jordan Normal Form is a way of representing a square matrix as a diagonal matrix with blocks of repeated eigenvalues on the main diagonal. It is named after the mathematician Camille Jordan.

How is Jordan Normal Form calculated?

To calculate the Jordan Normal Form of a matrix, you first need to find the eigenvalues of the matrix. Then, for each eigenvalue, you find the corresponding eigenvectors and use them to construct the Jordan blocks. Finally, you put these blocks together to form the Jordan Normal Form.

Why is Jordan Normal Form important?

Jordan Normal Form is important because it simplifies the calculation of powers and inverses of matrices. It also provides insights into the structure of a matrix and its relationship to its eigenvalues and eigenvectors.

What is a Jordan basis?

A Jordan basis is a set of vectors that form a basis for the vector space on which a matrix operates. These vectors are chosen in such a way that the Jordan Normal Form of the matrix is easily obtained.

How is a Jordan basis calculated?

To calculate a Jordan basis, you first need to find the eigenvalues of the matrix. Then, for each eigenvalue, you find the corresponding eigenvectors and use them to construct the Jordan basis. This basis is not unique and may vary depending on the choice of eigenvectors.

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