Can a non-symmetric matrix be positive definite?

In summary: Therefore, if A is positive definite, then A_S is also positive definite, because x^TA_Sx > 0 for all x vector. In summary, a real nxn matrix A must be symmetric for A+AT to be positive definite. There is a condition on the eigenvalues of A, where all eigenvalues must be positive for A+AT to be positive definite. The definition of a positive definite matrix is not entirely clear, as some sources define it for non-symmetric matrices while others only consider symmetric matrices. However, for practical purposes, a positive definite matrix can be considered symmetric and the symmetric part of a positive definite matrix is also positive definite.
  • #1
Leo321
38
0
Let A be a real nxn matrix.
What are the requirements of A for A+AT to be positive definite?
Is there a condition on eigenvalues of A, so that A+AT is positive definite?

Also I am not sure about the definition of a positive definite matrix. In some places it is written that the matrix must be symmetric, while in others it is defined for non-symmetric matrices. In many places I see theorems, which require a matrix to be positive definite and it is not clear to me if I can use it for non-symmetric matrices or not.
 
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  • #3
Grufey said:
Hello.

First, the definition:

Let's a matrix, A, is called definite positive if, [tex]vAv^t>0[/tex] for all v (v vector).

Here, I think you have the answer.

http://mathworld.wolfram.com/PositiveDefiniteMatrix.html

The problem is that this differs from how it is defined in Wikipedia. The Wikipedia definition is clear about symmetric matrices, but vague about non symmetric ones. So what do you do when you see some theorem, that speaks about positive definite matrices? Do you require the matrix to be symmetric or not?
 
  • #4
I don't know if wikipedia is the ultimate source but definiteness is usually defined together with the partial ordering (actually Löewner partial ordering to sound very academic and sophisticated). Thus, non-hermitian definite matrices are of little use. Only gives some information about the sign of its eigenvalues. In other words [itex]A-B \succ 0[/itex] and thus [itex]A \succ B[/itex] makes no sense for nonhermitian matrices.

When the matrix entries are real [itex]v^tAv = v^TA^Tv \in \mathbb{R}[/itex], hence if [itex]v^TAv > 0[/itex] for all v , then [itex]v^T(A + A^T)v = 2v^TAv> 0[/itex] for all v. Note that, I did not use the term positive definite since A might be nonsymmetric. But obviously [itex]A + A^T[/itex] is symmetric hence positive definite.
 
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  • #5
Edited:

Positive definite matrix is automatically symmetric.

That was wrong in the real case. Thanks, D H.
 
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  • #6
arkajad said:
Positive definite matrix is automatically symmetric.
Not true. What can be said is that the symmetric part of a positive definite matrix is positive definite.

Any NxN matrix can be represented as a sum of a symmetric and antisymmetric (skew symmetric) matrices:

[tex]\begin{align*}
A &= A_S + A_A \\[4pt]
A_S &\equiv \frac 1 2 \left(A+A^T\right) \\[4pt]
A_A &\equiv \frac 1 2 \left(A-A^T\right)
\end{align*}[/tex]

With this notation, the quadratic form [itex]x^TAx[/itex] becomes

[tex]x^TAx = x^TA_Sx + x^TA_Ax = x^TA_Sx[/tex]

The final expression results because [itex]x^TA_Ax \equiv 0[/itex]. The contribution of the skew symmetric part of a matrix to this quadratic form is identically zero.
 

1. What is a positive definite matrix?

A positive definite matrix is a square matrix where all of its eigenvalues are positive. In other words, it is a symmetric matrix where all of its principal minors (sub-matrices formed by deleting rows and columns) have a positive determinant.

2. What are the properties of a positive definite matrix?

Some key properties of a positive definite matrix include:

  • All of its eigenvalues are positive.
  • All of its principal minors have a positive determinant.
  • It is symmetric.
  • It is invertible.
  • It has a unique Cholesky decomposition.

3. How is a positive definite matrix used in mathematics and statistics?

Positive definite matrices are used in various fields such as linear algebra, optimization, and statistics. In linear algebra, they are used to define inner products and to prove the existence of orthogonal bases. In optimization, they are used to define positive definite quadratic forms and to determine the nature of critical points. In statistics, they are used in methods such as Principal Component Analysis and Maximum Likelihood Estimation.

4. How can a positive definite matrix be identified?

There are several ways to identify a positive definite matrix:

  • Check if all of its eigenvalues are positive.
  • Check if all of its principal minors have a positive determinant.
  • Check if it is symmetric and has all positive diagonal elements.
  • Check if it has a Cholesky decomposition (an upper triangular matrix with positive diagonal elements).

5. Can a positive definite matrix have negative eigenvalues?

No, a positive definite matrix cannot have negative eigenvalues. By definition, all of its eigenvalues must be positive. If a matrix has at least one negative eigenvalue, it is not positive definite.

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