Is {C, D} Independent? Proving Matrix Independence in 3 Simple Steps

In summary, if {C,D} were not a set of independent matrices then taking the transpose of both sides of said relation would tell you what numbers a and b not both zero could satisfy in order to make aC + bD=0.
  • #1
jumbogala
423
4
Edit: There was a mistake in the question, see below for right question.
 
Last edited:
Physics news on Phys.org
  • #2
If {C,D} was not a set of independent matrices then what sort of relation would C and D satisfy? What does taking the transpose of both sides of said relation tell you?
 
  • #3
If {C,D} were not a set of independent matrices, then I would be able to find some numbers a and b not both zero, such that aC + bD = 0.

Transpose of this... aCT + bDT = 0?
 
  • #4
Right, now use the relations given in the question to rewrite that last equation.
 
  • #5
Okay, so that means

aC + b(-D) = 0.

Now that means that aC + b(-D) = aC + bD

and can be rewritten aC -b(D) = aC + bD... which would mean that a = a, and -b = b. But the only way -b = b can be true is if b = 0. So therefore, b is zero and my initial condition is false, and they are independent! right?
 
  • #6
oh wait, but a can still be something other than zero... my condition is that they are not BOTH zero. so my initial condition is not necessarily false =/
 
  • #7
Sort of. You can't exactly just equate coefficients if that's what you did. The last equation you wrote implies that bD = 0 by just rearranging. You can't cancel the D here either, but you can use one property given in the question which you haven't used yet. :)
 
  • #8
Wait, why can't I cancel the D? If bD = 0 and D is not zero, then isn't b zero?

Am I supposed to use the fact that they are n x n?
 
  • #9
I just realized the question is not supposed to say that C and D are independent matrices, just that they are n x n and nonzero, if that makes a difference.
 
  • #10
Sure it makes a difference. You've got aC+bD=0 and aC-bD=0. To show C and D are independent, you want to show that a and b are both zero. Suppose a is nonzero?
 
  • #11
If it's still true that bD is zero, then if a is nonzero, you'd have aC is not zero.

Then aC + bD = 0 --> aC + 0 = 0 but if aC is not zero this is obviously not true.
 
  • #12
Add the two equations. Who cares what bD is? If a is nonzero then you get 2aC=0. a is nonzero, C is nonzero. Possible, or not?
 
  • #13
No, not possible. Therefore a must be zero.

But I still need to show that b is zero, right?

Now that I know a is zero can I just plug it into the equation aC + bD = 0?
 
  • #14
Sure you can. Or you could subtract the two equations and conclude 2bD=0, D being nonzero means b must be zero. Same conclusion either way.
 
  • #15
Great, so then a = b = 0, thus {C, D} is independent. And we're done!

Thanks to both of you for your help :)
 

1. What is a "Matrix Independence Proof"?

A "Matrix Independence Proof" is a mathematical technique used to determine whether a set of vectors (or matrices) in a given matrix are linearly independent or not. This proof is essential in many areas of mathematics and science, including linear algebra, computer graphics, and quantum mechanics.

2. How do you perform a Matrix Independence Proof?

To perform a Matrix Independence Proof, you need to set up an equation using the vectors (or matrices) in the given matrix and solve for the coefficients. If the only solution is when all the coefficients are equal to zero, then the vectors are linearly independent. If there is more than one solution, then the vectors are linearly dependent.

3. Why is Matrix Independence Proof important?

Matrix Independence Proof is important because it allows us to determine whether a set of vectors (or matrices) can be used as a basis for a vector space. This is crucial in many mathematical and scientific applications, such as solving systems of equations, finding eigenvalues and eigenvectors, and performing transformations in computer graphics.

4. What are some real-world applications of Matrix Independence Proof?

Matrix Independence Proof has various real-world applications, such as image and signal processing, data compression, and cryptography. It is also used in engineering fields like control systems and signal processing to analyze and design systems.

5. Are there any limitations to Matrix Independence Proof?

Yes, there are some limitations to Matrix Independence Proof. It only applies to finite-dimensional vector spaces, so it cannot be used for infinite-dimensional vector spaces. Also, it is not able to determine if a set of vectors is linearly independent if there are more vectors than the dimension of the vector space.

Similar threads

  • Calculus and Beyond Homework Help
Replies
1
Views
259
  • Calculus and Beyond Homework Help
Replies
2
Views
972
  • Calculus and Beyond Homework Help
Replies
6
Views
882
  • Calculus and Beyond Homework Help
Replies
2
Views
365
  • Calculus and Beyond Homework Help
Replies
8
Views
1K
  • Calculus and Beyond Homework Help
Replies
3
Views
312
  • Calculus and Beyond Homework Help
Replies
4
Views
1K
  • Calculus and Beyond Homework Help
Replies
3
Views
2K
  • Calculus and Beyond Homework Help
Replies
7
Views
2K
  • Calculus and Beyond Homework Help
Replies
1
Views
1K
Back
Top