Prove the Matrix Inequalities Theorem

In summary, this theorem states that if A, B, C, and D are matrices of the same size, then (a) if A ≤ B and B ≤ C, then A ≤ C; (b) if A ≤ B and C ≤ D, then A + C ≤ B + D; and (c) if A ≤ B, then cA ≤ cB for any positive constant c and cA >= cB for any negative constant c. This theorem must be proven using arbitrary matrices with specified sizes and entries.
  • #1
csc2iffy
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Homework Statement



Theorem:
Suppose A, B, C, and D are matrices of the same size. Then
a) If A ≤ B and B ≤ C, then A ≤ C
b) If A ≤ B and C ≤ D, then A + C ≤ B + D
c) If A ≤ B, then cA ≤ cB for any positive constant c and cA >= cB for any negative constant c

Prove this theorem. Must use arbitrary matrices, one where both the size and entries are specified as variables

Homework Equations





The Attempt at a Solution



Let A=[ai,j], B=[bi,j], C=[ci,j], D=[di,j]

a) Let (1) [ai,j] ≤ [bi,j]
(2) [bi,j] ≤ [ci,j]
Adding (1) and (2), we get
[ai,j] + [bi,j] ≤ [bi,j] + [ci,j]
Subtracting [bi,j] from both sides,
[ai,j] ≤ [ci,j]
Therefore A ≤ C

b) Let (1) [ai,j] ≤ [bi,j]
(2) [ci,j] ≤ [di,j]
Adding (1) and (2), we get
[ai,j] + [ci,j] ≤ [bi,j] + [di,j]
Therefore A + C ≤ B + D

c) Not really sure how to do c?
 
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  • #2
what is the definition of <= for matrices?
 
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First, tell us what it means to say matrix A ≤ matrix B. You have to know your definitions in math.
 
  • #6
OK. this proof is in my linear programming class. I cannot remember what this means.. she did not give us a recap on inequalities of matrices
 
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  • #7
Ya, you are on the right track and "c" is related to inequalities in algebra.
 
  • #8
csc2iffy said:
OK. this proof is in my linear programming class. I cannot remember what this means.. she did not give us a recap on inequalities of matrices
Then how can you possibly know what properties matrix inequalities have? Like how do you know that A+B ≤ B+C implies A ≤ C? It's true for real numbers, but you can't automatically assume it holds for matrices.

Don't you have a textbook you can consult for basic definitions?
 
  • #10
nope my textbook just goes into the matrices of LP problems, not their properties :(
i just assumed it worked with matrices as it does with regular numbers, since any entry in A or B is just a number... so my attempt is completely wrong?
 
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  • #11
Well, it depends. If I had to guess, perhaps A, B, C, D are square matrices of the same size and the ordering is on the determinants of those matrices?

Could you post more context?
 
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  • #14
In (a), for all i,j, ai,j ≤ bi,j, and bi,j ≤ ci,j implies what about the relationship between the elements of A and C?

Proceed similarly for the other parts.

dirk_mec1's link may be helpful. micromass' link delves a bit too deep to be useful.

If you want, you can go deeper with respect to this problem. The definition is an example of a http://en.wikipedia.org/wiki/Partial_order
 
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  • #16
Notation-wise, I'd remove the square brackets because you're talking about the specific elements of each matrix. Note that they don't use the square brackets in the definition you cited. Otherwise, they look good.
csc2iffy said:
Since A ≤ B, then ai,j ≤ bi,j for all i,j entries of A and B.

Since B ≤ C, then bi,j ≤ ci,j for all i,j entries of B and C.

For all i,j entries, since ai,j ≤ bi,j and bi,j ≤ ci,j, then, by the [STRIKE]transient[/STRIKE] transitive property of inequalities, ai,j ≤ ci,j.

Therefore A ≤ C.
 

FAQ: Prove the Matrix Inequalities Theorem

What is the Matrix Properties Theorem?

The Matrix Properties Theorem is a mathematical theorem that states the properties of matrices and how they behave under certain operations, such as addition, multiplication, and inversion. It is used to solve problems in linear algebra and is essential in many areas of science and engineering.

What are the key properties of matrices described in the theorem?

The key properties of matrices described in the theorem include commutativity, associativity, distributivity, and identity. Commutativity states that the order of multiplication of matrices does not affect the result. Associativity states that the grouping of matrices in a multiplication does not affect the result. Distributivity states that multiplying a matrix by a sum of other matrices is equal to the sum of each individual matrix multiplied by the first matrix. Identity states that the identity matrix, when multiplied by any other matrix, results in the same matrix.

How is the Matrix Properties Theorem used in science?

The Matrix Properties Theorem is used in science to solve problems related to linear transformations, such as in physics, chemistry, and biology. It is also used in computer science and engineering for data manipulation and image processing algorithms.

Can the Matrix Properties Theorem be applied to all types of matrices?

Yes, the Matrix Properties Theorem can be applied to all types of matrices, including square matrices, rectangular matrices, and even complex matrices. However, some properties may not hold for non-square matrices, such as the existence of an inverse matrix.

Is the Matrix Properties Theorem only applicable to matrices with real numbers?

No, the Matrix Properties Theorem is applicable to matrices with any type of numbers, including real numbers, complex numbers, and even matrices with variables. The properties hold for any type of number as long as the operations used are valid for that type of number.

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