What is a Right Hand Side Vector in Eigenvector Calculations?

In summary, the eigenvalues of an matrix are 1, 1/2, and 1/3. You need to find the constants c1, c2, and c3 so that the eigenvectors k1, k2, and k3 form a linear combination of them. Once you have the constants, you can solve for Ane1.
  • #1
thunderbird
16
0

Homework Statement



I've done part A, and part D is easy. I'm stuck with part B. I have no idea what a "right hand side vector" is...

HtQcr.png


Homework Equations





The Attempt at a Solution



Part A: All eigenvectors are valid. Eigenvalues are 1, 1/2 and 1/3.
 
Physics news on Phys.org
  • #2
thunderbird said:

Homework Statement



I've done part A, and part D is easy. I'm stuck with part B. I have no idea what a "right hand side vector" is...
Write each of the vectors e1, e2, and e3 as a linear combination of k1, k2, and k3.

The idea is to write Ane1 as An(c1k1 + c2k2 + c3k3).

thunderbird said:
HtQcr.png


Homework Equations





The Attempt at a Solution



Part A: All eigenvectors are valid. Eigenvalues are 1, 1/2 and 1/3.
 
  • #3
How do I find the constants and the e vectors? I don't think I really understand what what I'm supposed to do represents...
 
  • #4
The ei are just the standard basis vectors for R3.
e1 = <1, 0, 0>T
e2 = <0, 1, 0>T
e3 = <0, 0, 1>T

You must have been taught how to write a vector (such as k1) as a linear combination of other vectors. Check your book and/or notes.
 
  • #5
I looked but it doesn't really say. We don't have a textbook for this actually and the notes are very vague. This is what it says:

We can write
x(0) = c1 k1 + c2 k2 + c3 k3 + c4 k4 (6.2)
for some coefficients c1 , c2 , c3 and c4 uniquely determined. Equation (6.2) can
be written in matrix-vector form
T c = x(0) (6.3)
where c = (c1 , c2 , c3 , c4 )T and T is the 4
× 4 matrix with eigenvectors k1 , k2 , k3
and k4 in its columns. Solving (6.3) (I used MATLAB) gives c1 = 1/2, c2 = 1/2,
c3
≈ −0.6830 and c4 ≈ 0.1830. With these values of c (6.2) is a representation
of x(0) as a linear combination of eigenvectors of P .
 
  • #6
thunderbird said:
I looked but it doesn't really say. We don't have a textbook for this actually and the notes are very vague. This is what it says:

We can write
x(0) = c1 k1 + c2 k2 + c3 k3 + c4 k4 (6.2)
for some coefficients c1 , c2 , c3 and c4 uniquely determined. Equation (6.2) can
be written in matrix-vector form
T c = x(0) (6.3)
where c = (c1 , c2 , c3 , c4 )T and T is the 4
× 4 matrix with eigenvectors k1 , k2 , k3
and k4 in its columns. Solving (6.3) (I used MATLAB) gives c1 = 1/2, c2 = 1/2,
c3
≈ −0.6830 and c4 ≈ 0.1830. With these values of c (6.2) is a representation
of x(0) as a linear combination of eigenvectors of P .

Put this in terms of what you have. You want to find constants c1, c2, c3 so that
e1 = c1 k1 + c2 k2 + c3 k3

and the same thing (with different sets of constants) for e2 and e3.

Then you can calculate Ane1 = An(c1 k1 + c2 k2 + c3 k3).
This works out to c1 An k1 + c2 An k2 + c3 An k3.

Since the ki's are eigenvectors, you can calculate A ki, and hopefully you have learned something about the eigenvalues of An.
 
  • #7
Ok like this?:

e1 = k1 - k2 + k3
e2 = 2 k1 + 0 k2 + k3
e3 = 0 1 0

Now what? I think I need to understand what's going on, not just what I need to do...
 

1. What is a matrix eigenvalue and eigenvector?

A matrix eigenvalue is a scalar value that represents the factor by which an eigenvector is stretched or compressed when it is multiplied by a transformation matrix. An eigenvector is a non-zero vector that remains in the same direction after being multiplied by a transformation matrix.

2. How are eigenvalues and eigenvectors calculated?

Eigenvalues and eigenvectors can be calculated by solving the characteristic equation for a given matrix. The characteristic equation is found by subtracting the eigenvalue from the diagonal elements of the matrix and then finding the determinant of the resulting matrix.

3. What is the significance of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are important in many areas of mathematics and science, particularly in linear algebra and quantum mechanics. They provide valuable information about the properties and behavior of a matrix, such as its stability, convergence, and transformation characteristics.

4. Can a matrix have more than one eigenvector?

Yes, a matrix can have multiple eigenvectors associated with the same eigenvalue. In fact, the number of eigenvectors for a given eigenvalue is known as the algebraic multiplicity of that eigenvalue.

5. How are eigenvalues and eigenvectors used in data analysis?

Eigenvalues and eigenvectors are commonly used in data analysis techniques such as principal component analysis (PCA) and singular value decomposition (SVD). These methods use eigenvalues and eigenvectors to identify and extract important patterns and features from large datasets.

Similar threads

  • Calculus and Beyond Homework Help
Replies
2
Views
87
  • Calculus and Beyond Homework Help
Replies
12
Views
1K
  • Calculus and Beyond Homework Help
Replies
7
Views
1K
  • Calculus and Beyond Homework Help
Replies
8
Views
2K
  • Calculus and Beyond Homework Help
Replies
4
Views
1K
  • Calculus and Beyond Homework Help
Replies
6
Views
1K
  • Calculus and Beyond Homework Help
Replies
13
Views
2K
  • Calculus and Beyond Homework Help
Replies
4
Views
2K
  • Calculus and Beyond Homework Help
Replies
5
Views
2K
  • Calculus and Beyond Homework Help
Replies
19
Views
3K
Back
Top