Positive Definiteness of a Real Matrix

In summary, the conversation discusses the positive definiteness of three matrices A, B, and C. The necessary and sufficient conditions for a real symmetric matrix to be positive definite are listed as a) xTAx greater than 0 for all nonzero real vectors x, b) all eigenvalues of A are greater than 0, c) all upper left submatrices of A have positive determinants, and d) all pivots (without row exchanges) are greater than 0. It is mentioned that A fails tests b, c, and d, while B and C pass test c and are considered positive definite. The significance of test (a) is also clarified.
  • #1
tatianaiistb
47
0

Homework Statement



Decide for or against the positive definiteness of

[2 -1 -1
-1 2 -1 = A
-1 -1 2]

[2 -1 -1
-1 2 1 = B
-1 1 2]

[5 2 1
2 2 2 = C
1 2 5]

Homework Equations



Each of the following tests is a necessary and sufficient condition for the real symmetric matrix A to be positive definite:
a) xTAx greater than 0 for all nonzero real vectors x.
b) All the eigenvalues of A are greater than 0
c) All the upper left submatrices of A have positive determinants
d) All the pivots (without row exchanges) are greater than 0.

The Attempt at a Solution



For matrix A,
I found that it fails tests b,c and d. I'm a bit confused because when I performed test a with vector x = [ 1 2 3 ] ^T the test passes, but with an x = [1 1 1]^T the test fails. Therefore, I said that it is not positive definite, but I'm unsure on this one.

For matrices B and C, I said that they are both positive definite because they both pass test c. I'm assuming that if it passes one of the tests it is sufficient.

Am I thinking correctly? Thanks!
 
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  • #2
Hi tatianaiistb! :smile:

Yes, it is sufficient if a matrix passes one of the tests.
Each test is equivalent to each other test.

Note that for test (a) the test has to pass for ALL nonzero real vectors.
In other words, this is not a practical test.
 
  • #3
tatianaiistb said:

Homework Statement



Decide for or against the positive definiteness of

[2 -1 -1
-1 2 -1 = A
-1 -1 2]

[2 -1 -1
-1 2 1 = B
-1 1 2]

[5 2 1
2 2 2 = C
1 2 5]

Homework Equations



Each of the following tests is a necessary and sufficient condition for the real symmetric matrix A to be positive definite:
a) xTAx greater than 0 for all nonzero real vectors x.
b) All the eigenvalues of A are greater than 0
c) All the upper left submatrices of A have positive determinants
d) All the pivots (without row exchanges) are greater than 0.

The Attempt at a Solution



For matrix A,
I found that it fails tests b,c and d. I'm a bit confused because when I performed test a with vector x = [ 1 2 3 ] ^T the test passes, but with an x = [1 1 1]^T the test fails. Therefore, I said that it is not positive definite, but I'm unsure on this one.

For matrices B and C, I said that they are both positive definite because they both pass test c. I'm assuming that if it passes one of the tests it is sufficient.

Am I thinking correctly? Thanks!

Note: (a) is the definition of positive-definiteness; it is not a test at all.
 
  • #4
So, if it fails one test it is sufficient to say that it is not positive definite, and viceversa? Thanks!
 
  • #5
Yep!
 

1. What does it mean for a matrix to be positive definite?

A matrix is positive definite if all of its eigenvalues are positive. In other words, a positive definite matrix is one that has all positive pivots when reduced to row echelon form.

2. How is positive definiteness related to symmetric matrices?

A real symmetric matrix is positive definite if and only if all of its eigenvalues are positive. This means that the matrix must have all positive pivots, and this can be easily checked by reducing the matrix to row echelon form.

3. Can a matrix be positive definite if it has negative eigenvalues?

No, a matrix cannot be positive definite if it has any negative eigenvalues. This is because a positive definite matrix must have all positive pivots, which is not possible if there are any negative eigenvalues present.

4. How is positive definiteness related to positive semi-definiteness?

A matrix is positive semi-definite if all of its eigenvalues are either positive or zero. This means that a positive definite matrix is also positive semi-definite, but the converse is not always true.

5. Can a matrix be positive definite if it has complex eigenvalues?

No, a matrix cannot be positive definite if it has any complex eigenvalues. This is because a positive definite matrix must have all real and positive eigenvalues, which is not possible if there are any complex eigenvalues present.

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