Eigenvalues and eigenvectors of a non-symmetric matrix?

In summary, the conversation revolves around finding the eigenvalues and eigenvectors of a non-symmetric matrix AB, where A and B are both symmetric matrices. The author suggests using the eigenvalues and eigenvectors of B^(1/2)*A*B^(1/2) to find those of AB, but the proposed solution does not seem to work. A forum discussion mentions that the product of two symmetric matrices may not have the same properties as the individual matrices themselves.
  • #1
prajeesh
1
0
I have a non symmetric matrix AB where A and B are symmetric matrices. How can I find the eigenvectors and eigenvalues of AB?

In a paper( Fisher Linear Discriminant Analysis by M Welling), the author asks to find eigenvalues and eigenvectors of B^(1/2)* A *B^(1/2) which is a symmetric matrix. But how can I get eigenvalues and eigenvectors of $AB$ from eigenvalues and eigenvectors of B^(1/2) A B^(1/2)?

Could someone please help me?

I tried the solution suggested by others. But it doesn't work
A=
[2,-1,0;
-1,2,-1;
0,-1,2];
B=
[32,-12,8;
-12,34,-21;
8,-21,13];

eigenvectors of AB=[0.516537330395033,-0.781188319935242,-0.0177964973702446;-0.710088559129181,-0.185707982205180,0.521054279012559;0.478501227273470,0.596034692062496,0.853337988726655];

eigenvectors of B^(1/2)* A* B^(1/2)= [0.517933641073670,-0.855373946305353,-0.00895295628145857;-0.725005239437560,-0.444501257554748,0.526104585439372;0.453995755742558,0.265996323309655,0.850372747536919];

product of B^(-1/2) and eigenvectors of B^(1/2)* A *B^(1/2) =[0.0692193234209673,-0.179045453961740,-0.160160577798552;-0.0951564325356731,-0.0425635779871867,4.68925725410385;0.0641222410443052,0.136608931923259,7.67966316565345];

Both are different. Is there any mistake in what I did?
 
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  • #3
Product of two symmetric matrices doesn’t possesses nice properties unless the matrices commute (in that case the product is also symmetric). It can be non-diagonalizable. Even it is diagonalizable, there is, in general, no correspondence between eigenvectors of A B and of factors themselves.
 

1. What are eigenvalues and eigenvectors of a non-symmetric matrix?

Eigenvalues and eigenvectors are mathematical concepts used to analyze the properties of a matrix. In a non-symmetric matrix, the eigenvalues and eigenvectors represent the characteristics of the matrix that do not change when the matrix is multiplied by a specific vector.

2. How do eigenvalues and eigenvectors differ in a non-symmetric matrix compared to a symmetric matrix?

In a symmetric matrix, the eigenvalues and eigenvectors are always real numbers. However, in a non-symmetric matrix, the eigenvalues can be complex numbers. Additionally, the eigenvectors in a non-symmetric matrix may not be orthogonal, unlike in a symmetric matrix.

3. How are eigenvalues and eigenvectors calculated for a non-symmetric matrix?

The eigenvalues of a non-symmetric matrix can be found by solving the characteristic equation, det(A-λI) = 0, where A is the matrix and λ is the eigenvalue. The corresponding eigenvectors can be found by solving the equation (A-λI)v = 0, where v is the eigenvector.

4. What is the significance of eigenvalues and eigenvectors in a non-symmetric matrix?

Eigenvalues and eigenvectors in a non-symmetric matrix help to understand the behavior of a system or process represented by the matrix. They can be used to determine the stability of a system and the direction of change in the system.

5. Can a non-symmetric matrix have repeated eigenvalues?

Yes, a non-symmetric matrix can have repeated eigenvalues. This means that there may be more than one eigenvector corresponding to the same eigenvalue. In this case, the matrix is said to have a degenerate eigenvalue.

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