Find the basis for both eigenvalues

In summary, the conversation discusses finding the basis for both eigenvalues of a given matrix by using diagonalization method and solving equations. The conversation also clarifies that row reduction cannot be used to determine the basis.
  • #1
LosTacos
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Homework Statement



Given matrix A= {[39/25,48/25],[48/25,11/25]} find the basis for both eigenvalues.


Homework Equations





The Attempt at a Solution



I row reduced the matrix and found both eigenvalues. I found λ = -1, and λ = 3. Then, I used diagonalization method [-1I2 - A 0] and [3I2 - A 0]. I got a basis of {[1,-3/4]} and {[1,4/3]}. However, I checked these but these were incorrect. I wasn't sure what I did wrong.
 
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  • #2
Row reduce the matrix? You can't find eigenvalues by row reduction!

If [x, y] is an eigenvector corresponding eigenvalue -1, then
[tex]\begin{bmatrix}\frac{39}{25} & \frac{48}{25} \\ \frac{49}{25} & \frac{11}{25}\end{bmatrix}\begin{bmatrix}x \\ y \end{bmatrix}= \begin{bmatrix}-x \\ -y\end{bmatrix}[/tex]

[tex]\begin{bmatrix}\frac{39}{25}x+ \frac{48}{25}y \\ \frac{48}{25}x+ \frac{11}{25}y\end{bmatrix}= \begin{bmatrix}-x \\ -y \end{bmatrix}[/tex]

So we must have [itex]39x/25+ 48y/25= -x[/itex], which is the same as [tex]64x+ 48y= 0[/tex] and [tex]48x/25+ 11y/25= -y[/tex] which is the same as [tex]48x+ 36y= 0[/tex].

Both of those equations reduce to a single equation of the form ax+ by= 0 so that y= (b/a)x.

If [x, y] is an eigenvector corresponding eigenvalue 3, then
[tex]\begin{bmatrix}\frac{39}{25} & \frac{48}{25} \\ \frac{49}{25} & \frac{11}{25}\end{bmatrix}\begin{bmatrix}x \\ y \end{bmatrix}= \begin{bmatrix}3x \\ 3y\end{bmatrix}[/tex]

[tex]\begin{bmatrix}\frac{39}{25}x+ \frac{48}{25}y \\ \frac{48}{25}x+ \frac{11}{25}y\end{bmatrix}= \begin{bmatrix}-x \\ -y \end{bmatrix}[/tex]

So we must have [itex]39x/25+ 48y/25= 3x[/itex], which is the same as [tex]-36x+ 48y= 0[/tex] and [tex]48x/25+ 11y/25= 3y[/tex] which is the same as [tex]48x- 64y= 0[/tex]. Again, both of those equations reduce to a single equation.
 
  • #3
Okay, so given those two solutions, do I row reduce it to determine teh basis?
 
  • #4
LosTacos said:
Okay, so given those two solutions, do I row reduce it to determine teh basis?
No. The first equation in HallsOfIvy's post is 48x + 36y = 0, which is equivalent to 4x + 3y = 0. From that equation you can find the eigenvector that is associated with the eigenvalue λ = -1.

The second equation is 48x - 64y = 0, or 3x - 4y = 0. Use this equation to find the eigenvector that is associated with the eigenvalue λ = 3.
 
  • #5
thank you
 
Last edited:

FAQ: Find the basis for both eigenvalues

1. What is the concept of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are concepts in linear algebra that are used to describe the behavior of a linear transformation on a vector space. Eigenvalues are scalar values that represent the scaling factor of the transformation, while eigenvectors are the corresponding vectors that do not change direction under the transformation.

2. How do you find the eigenvalues of a matrix?

To find the eigenvalues of a matrix, you need to solve the characteristic equation, which is det(A-λI) = 0, where A is the matrix and λ is the eigenvalue. This equation will give you the values of λ that satisfy the equation, and these values are the eigenvalues of the matrix.

3. What is the significance of finding the basis for eigenvalues?

Finding the basis for eigenvalues allows us to understand the behavior of a linear transformation in a vector space. It helps us to identify the directions in which the transformation does not change, and these directions are represented by the eigenvectors. Additionally, the basis for eigenvalues can be used to diagonalize a matrix, making it easier to perform calculations and solve problems.

4. Can a matrix have more than one basis for its eigenvalues?

Yes, a matrix can have multiple bases for its eigenvalues. This is because there can be multiple eigenvectors for a single eigenvalue, and these eigenvectors form a basis for that eigenvalue. Additionally, a matrix can have distinct eigenvalues with their own corresponding bases.

5. How do you use eigenvalues to solve real-world problems?

Eigenvalues and eigenvectors have many applications in real-world problems, such as image and signal processing, data compression, and optimization. They can also be used in physics to describe the behavior of physical systems, and in economics to model financial data. By understanding the basis for eigenvalues, we can use them to analyze and solve these types of problems.

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