Linear Algebra - Eigenvector question

In summary, the linear operator T on R2 with the matrix [[4, -5], [-4, -3]] relative to the basis {(1,2), (0,1)} has eigenvalues of 8 and -1. To find the eigenvectors, the matrix is solved for each eigenvalue, resulting in the eigenvectors (-5/4, 1) and (-5, -6) when written in the given basis. To obtain the eigenvectors in the standard basis, the fractions are cleared and the resulting vectors are (-5, 4) and (-5, -6) respectively.
  • #1
zeion
466
1

Homework Statement



The linear operator T on R2 has the matrix
[tex]

\begin{bmatrix}4&-5\\-4&-3 \end{bmatrix}

[/tex] relative to the basis {(1,2), (0,1)}
Find the eigenvalues of T, and obtain an eigenvector corresponding to each eigenvalue.


Homework Equations





The Attempt at a Solution



So I solved the eigenvalues to be [tex]
\lambda = 8, \lambda = -1
[/tex]

I know I normally just sub in the lambda to the matrix and then solve for the null space to get the eigenvector, but how do I do it with a different basis?
 
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  • #2
Is that the right matrix? I get different eigenvalues than you do.

Oh, and to answer your question, you just solve for them like you usually do. The eigenvectors you find will be represented in the given basis.
 
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  • #3
Oh sorry it's supposed to be a 3 not -3..
So then I solve for it like this?

For lambda = 8
[tex] \begin{bmatrix}4&-5\\-4&3 \end{bmatrix} \rightarrow \begin{bmatrix}-4&-5\\-4& -5 \end{bmatrix} \rightarrow \begin{bmatrix}1&5/4\\0& 0 \end{bmatrix}

[/tex]

Then the vector is (-5/4, 1)?

But the answer in the book is (-5, -6) :/

Ok I think I see what they did.. just multiplied it by 4 to get rid of the fraction and then wrote it wrt to the standard basis?
 
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  • #4
Yup, that's what they did.
 
  • #5
vela said:
Yup, that's what they did.

Hi, could you just help me with the part where they write it wrt to the basis? It sort of confuses me.

I understand we get (-5/4 1), and once clearing the fraction we get (-5, 4). But how does this jump to (-5, -6)?
 
  • #6
-5(1,2) + 4(0,1)
 

FAQ: Linear Algebra - Eigenvector question

What is a eigenvector?

An eigenvector is a vector that, when multiplied by a square matrix, results in a scalar multiple of itself. In other words, the direction of the vector does not change, but its magnitude is multiplied by a constant factor.

How is an eigenvector different from a regular vector?

While a regular vector can be transformed by a matrix to any other vector, an eigenvector remains in the same direction after the transformation, only changing in magnitude.

How do you find eigenvectors?

To find eigenvectors, you need to first find the eigenvalues of a matrix. Then, you can use the eigenvalues to solve for the corresponding eigenvectors using a system of linear equations.

What is the significance of eigenvectors in linear algebra?

Eigenvectors are important in linear algebra because they represent the directions along which a linear transformation only scales the input, without changing its direction. They can also be used to simplify complex matrix operations and solve differential equations.

Can there be more than one eigenvector for a single eigenvalue?

Yes, it is possible for a single eigenvalue to have multiple eigenvectors. In fact, there can be an infinite number of eigenvectors for a single eigenvalue, as long as they are linearly independent.

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