How to Express a Vector as a Linear Combination of Eigenvectors?

In summary, the conversation discusses finding the linear combination of a given vector as a combination of two eigenvectors. The solution involves solving a linear system and the answer should be in the form of variables a1 and a2.
  • #1
Angello90
65
0
Hey guys,

I'm studing to my exams now, and I came accors this question i eigenvectors where you find them and bla bla. There is part to it which asks to express vetor

X= [2/1]

as a linear combination of eigenvectors. Hence calculate B2X, B3X, B4X and B51X, simplifying your answers as much as possible.

How do you do the linear combination?

Thanks!
 
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  • #2
The "bla bla" does not help at all. Perhaps you could post the entire question?

For example, what does "[2/1]" mean? Is that a two dimensional vector with components 2 and 1? Write it as a linear combination of what eigenvectors? Is there some matrix or linear transformation you haven't mentioned? And what are " B2X, B3X, B4X and B51X"? Those are not standardized notations.
 
  • #3
Ok sorry I suppose I didn't make myself clear.

I have two eigenvectors.

First: Look at 1.jpg
Second : Look at 2.jpg

The vector X (look at 3.jpg) is to be written as a linear combination of eigenvectors. How do you do that? It's just a theory I'm interested in not solution to the question.

Thanks and sorry for inconvenience.
 

Attachments

  • 1.jpg
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  • 2.jpg
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  • 3.jpg
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  • #4
OK, now your question is clear. Let v1=(-3,1) be the first eigenvector, and v2=(-2,1) the second one. Now you want "a1" and "a2" such that

X = a1 v1 + a2 b2

That is equivalent to solving a linear system

[2] = [-3 -2] [a1]
[1] [ 1 1] [a2]

Where the eigenvectors went as columns.
 
  • #5
So the answer should look like this (look at the ans.jpg)?
And are a1 and a2 variables?

Thanks a lot!
 

Attachments

  • ans.jpg
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  • #6
correct! :)
 
  • #7
Thanks a lot jrlaguna!
 

1. What are eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are concepts in linear algebra that are used to describe certain properties of a matrix. Eigenvalues represent the scalars that a matrix can be multiplied by without changing the direction of its corresponding eigenvector. Eigenvectors are the corresponding vectors that are only scaled by the eigenvalue when multiplied by the matrix.

2. How are eigenvalues and eigenvectors calculated?

Eigenvalues and eigenvectors can be calculated using a variety of methods, including the characteristic polynomial, diagonalization, and the power method. The most common method is diagonalization, which involves finding the eigenvalues and eigenvectors of a matrix by transforming it into a diagonal matrix using elementary row operations.

3. What is the significance of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are important in many areas of mathematics and science, including physics, chemistry, and computer science. They are used to solve systems of linear equations, study the behavior of dynamical systems, and perform data analysis and dimensionality reduction.

4. Can a matrix have more than one eigenvalue and eigenvector?

Yes, a matrix can have multiple eigenvalues and corresponding eigenvectors. In fact, a square matrix of size n will have n eigenvalues and n eigenvectors (assuming they are all distinct).

5. How are eigenvalues and eigenvectors used in real-world applications?

Eigenvalues and eigenvectors are used in a variety of real-world applications, such as image and signal processing, machine learning, and quantum mechanics. They are also used in engineering and physics to study vibrations and oscillations in systems, and in economics to analyze market trends.

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