What Are the Eigenvalues of A Transpose A?

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Homework Help Overview

The discussion centers around the eigenvalues of the matrix product ATA, where A is an m x n matrix with rank m, indicating that m is less than n. The original poster explores the implications of this setup, particularly regarding the existence of eigenvalues and the specific case of zero being an eigenvalue.

Discussion Character

  • Exploratory, Assumption checking, Conceptual clarification

Approaches and Questions Raised

  • The original poster attempts to demonstrate that zero is an eigenvalue of ATA and questions what additional information can be derived about the eigenvalues of this matrix. Other participants introduce concepts related to the spectral theorem and its relevance to symmetric matrices, while also questioning the necessity of that theorem in this context.

Discussion Status

The discussion is active, with participants exploring different aspects of the eigenvalue problem. Some guidance has been provided regarding the implications of multiplying the eigenvalue equation by xT, and there is an ongoing exploration of the relationship between the properties of symmetric matrices and the eigenvalues of ATA.

Contextual Notes

Participants note that the spectral theorem was not covered in their course, which may limit the depth of discussion regarding the diagonalizability of the matrix in question. There is also a recognition of the constraints imposed by the course content on the exploration of eigenvalues.

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Homework Statement



Let A be an m x n matrix with rank(A) = m < n. As far as the eigenvalues of A^{T}A is concerned we can say that...

Homework Equations





The Attempt at a Solution



If eigenvalues exist, then

A^{T}Ax = λx where x ≠ 0.

The only thing I think I can show is that 0 is an eigenvalue:

If 0 is an eigenvalue for A^{T}A then

A^{T}Ax = (0)x where x ≠ 0.

N(A) ≠ {0}, so Ax = 0 where x ≠ 0.

Therefore A^{T}(Ax) = 0 where x ≠ 0. So λ = 0 is an eigenvalue for A^{T}A.

Is there anything else that can be said about the eigenvalues for this matrix?
 
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Did you hear about the spectral theorem for symmetric matrices?
 
No, that wasn't covered in my course so I suppose that's not what the professor is looking for. Is it relatively ea
 
3.141592654 said:
No, that wasn't covered in my course so I suppose that's not what the professor is looking for. Is it relatively ea

If A^T*A*x=lambda*x what happens if you multiply both sides on the left by x^T? No, you don't need the spectral theorem.
 
3.141592654 said:
No, that wasn't covered in my course so I suppose that's not what the professor is looking for. Is it relatively ea

Spectral theorem says that a symmetric matrix is diagonalizable.
In particular, a real nxn symmetric matrix has n real eigenvalues.
 

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