How to Use Cholesky Factorization for Positive Definite Matrices

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freshnitesh
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Homework Statement



Textbook exercise 6.1.7: find symmetric matrices A1 and A2 for f1 = x1^2 + x2^2 + x3^2 - 2x1x2 - 2x1x3 + 2x2x3 and f2 = x1^2 + 2x2^2 + 11x3^2 - 2x1x2 - 2x1x3 - 4x2x3; parts b and c below.


2. The attempt at a solution

So part a. makes sense to me, it basically comes down to

A1 =
1 -1 -1
-1 1 1
-1 1 1

A2 =
1 -1 -1
-1 2 -2
-1 -2 11

I'm not sure how to approach part b. because the question doesn't make much sense to me. It's asking to show that f1 is a single perfect square, so my guess is that from A1 I have to derive an expression for f1 that is a single perfect square.

Haven't really looked to hard at part c, yet.
 
freshnitesh said:

Homework Statement



Textbook exercise 6.1.7: find symmetric matrices A1 and A2 for quadratic forms f1 = x1^2 + x2^2 + x3^2 - 2x1x2 - 2x1x3 + 2x2x3 and f2 = x1^2 + 2x2^2 + 11x3^2 - 2x1x2 - 2x1x3 - 4x2x3, with parts b and c.


2. The attempt at a solution

So part a. makes sense to me, it basically comes down to

A1 =
1 -1 -1
-1 1 1
-1 1 1

A2 =
1 -1 -1
-1 2 -2
-1 -2 11

I'm not sure how to approach part b. because the question doesn't make much sense to me. It's asking to show that f1 is a single perfect square, so my guess is that from A1 I have to derive an expression for f1 that is a single perfect square.

Haven't really looked to hard at part c, yet.

Use Chpolesky factorization, which works for any positive-semidefinite matrix. (Many discussions assume positive definiteness, but if you go through the material carefully you can show that it applies as well to the semidefinite case.) See, eg., http://en.wikipedia.org/wiki/Cholesky_decomposition .
In fact, using the Cholesky algorithm is by far the easiest way to test positive definitness or semidefinitness---much easier than dealing with determinants, for example.