Seeking of eigenvalues and eigenvectors of a given matrix

In summary, the homework statement asks if it is permissible to simplify a matrix by means of elementary row operations. The answer is no, because the eigenvalues and eigenvector of the simplified matrix are not invariant with respect to these operations.
  • #1
annoymage
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Homework Statement



in seeking of eigenvalues and eigenvectors of a given matrix A, is it permissible first to simplify A by means of some elementary operation? (that is, are the eigenvalues and eigenvector of A invariant with respect to elementary row operation)? (prove it)

Homework Equations



n/a

The Attempt at a Solution



i want to prove it, but before that i want to translated it correctly

F is a field, v is eigenvector, λ is eigenvalue

Given A[tex]\in[/tex]Mnxn(F)

if B is row equivalent to A, then there exist unique λ[tex]\in[/tex]F and v such that
Av=λv=Bv

so, is my translation correct?
 
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  • #2
No, unfortunately eigenvalues are changed by "row operations" and so "simplifying" a matrix that way does not help.
 
  • #3
yes i know, i got counter example, but i wan to try to prove it systematically,

if B is row equivalent to A, then there exist unique λF and v such that
Av=λv=Bv,

so maybe i can proof by contradiction or something, but is that statement really same as the question?
 
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  • #4
or i simply just give the counterexample? and done proof?
 
  • #5
Unless you are explicitly asked for a proof, a counterexample is enough
 
  • #6
unless it says "for all elementary matrices" then counter example is ok

but it said "for some elementary matrices", right?

now I'm still rereading all my lecture notes on logic, help me if you can, with the logic owhoo,
 
  • #7
can i do like this

Suppose A=(En...E2E3)B and there exist unique v and λ such that Av=λv and Bv=λv

then, when λ and v is unique then λv is unique which imply Av=Bv,

when v is unique, Av=Bv => A=B !

contradict the fact that A=(En...E2E3)B => A[tex]\neq[/tex]B

Conclusion, If A=(En...E2E3)B then Av[tex]\neq[/tex]λv or Bv[tex]\neq[/tex]λv for all v and λ

i this really correct? i can't tell whether I'm just doing thing to trivial, help T_T
 

FAQ: Seeking of eigenvalues and eigenvectors of a given matrix

What is the purpose of finding eigenvalues and eigenvectors of a matrix?

The purpose of finding eigenvalues and eigenvectors is to understand the behavior and transformations of the matrix. It allows us to identify important characteristics of the matrix, such as its dominant directions and scaling factors.

How do eigenvalues and eigenvectors relate to each other?

Eigenvalues and eigenvectors are closely related. An eigenvector is a vector that, when multiplied by a matrix, results in a scaled version of the original vector. The scale factor is the corresponding eigenvalue. In other words, the eigenvector determines the direction and the eigenvalue determines the magnitude of the transformation.

What is the significance of the determinant in finding eigenvalues and eigenvectors?

The determinant of a matrix is used to find the eigenvalues. It is a value that represents the scaling factor of the matrix transformation. The determinant is important because it allows us to determine if a matrix has any non-zero eigenvalues, which are crucial in finding eigenvectors.

Can a matrix have multiple eigenvalues and eigenvectors?

Yes, a matrix can have multiple eigenvalues and eigenvectors. In fact, most matrices have more than one eigenvalue and eigenvector. This is because there can be multiple directions and scaling factors in which the matrix can transform a vector.

How are eigenvalues and eigenvectors used in practical applications?

Eigenvalues and eigenvectors are used in various fields such as physics, engineering, economics, and computer science. They are used to understand the behavior of systems, analyze data, and solve complex problems. In particular, they are useful in applications involving linear transformations, such as image processing and data compression.

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