Linear Algebra : Rank of a matrix

In summary: Lin, a sophomore at MIT, has created a 3D printer that can create objects with infinite detail. This printer uses a lattice of rods that can create any shape or object.
  • #1
lax1113
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Homework Statement


Given the following conditions, determine if there are no solutions, a unique solution, or infinite solutions. (Matrix A|B = augmented matrix).

Just in case anyone viewing needs a little refresher... Rank = number of non zero rows in the matrix.

1)

# of equations : 3
# of unknowns : 4
Rank of Matrix A : -
Rank of Matrix A|B: 2

2)

# of equations : 4
# of unknowns : 4
Rank of Matrix A : 4
Rank of Matrix A|B: -


2. Homework Equations and attempt

So I know that for a system to be consistent, the rank of A has to be equal to the rank of A|B. At this point, if this is true, we can then go on to say that if the rank of A is less than the # of unknowns, then A has infinite solutions (Unknowns - Rank(A) = free parameters). The only thing that I am not sure about is how to determine the Rank of A given the other 3, or the rank of A|B. Is this question asking for multiple answers?

For example, for number one, would I say that in the case that Rank(A) is less than Rank A|B, the system is inconsistent, while if the rank of A is equal to that of A|B then the system is consistent with infinite solutions because A<unknowns? I feel like with the number of given equations I should be able to figure out the missing part, since with the way that I just looked at it I am basically completely ignoring the information given in the equations.

I am really stuck on how to find out the other rank (if it is even possible!) and I have an exam on this tomorrow, so any hint would be greatly appreciated. I couldn't find problems like this online or in my book at .

Thanks
 
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  • #2
lax1113 said:
Just in case anyone viewing needs a little refresher... Rank = number of non zero rows in the matrix.

not quite, from wiki
"The rank of a matrix A is the maximal number of linearly independent rows or columns of A"
http://en.wikipedia.org/wiki/Rank_(linear_algebra )
 
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  • #3
LaneDance,
Thank you for your reply. Would it be accurate to say than that in the first problem the rank of matrix A could be interpreted as being 3? Since there will be 3 rows so the maximum would be 3? And I don't know how to interpret when the rank of A is greater than the augmented matrix, I was under the impression that it was either equal to or less than A|B.

Also, for the rank of A|B as shown in problem 2, 4eqs,4unknowns, A has a rank of 4, I feel like A|B also would have to be 4.To add on to my first statement, I noticed that it said it was the lesser of mxn, so we would look at the rows to define the max rank.
And max rank = Rank A?
 
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  • #4
lax1113 said:
LaneDance,
Thank you for your reply. Would it be accurate to say than that in the first problem the rank of matrix A could be interpreted as being 3? Since there will be 3 rows so the maximum would be 3? And I don't know how to interpret when the rank of A is greater than the augmented matrix, I was under the impression that it was either equal to or less than A|B.
The max it could be is 3, but it should always be Rank (A) <= Rank(A|B)

lax1113 said:
Also, for the rank of A|B as shown in problem 2, 4eqs,4unknowns, A has a rank of 4, I feel like A|B also would have to be 4.
I would agree, it has to be 4, as A has 4 rows it can't be any larger
lax1113 said:
To add on to my first statement, I noticed that it said it was the lesser of mxn, so we would look at the rows to define the max rank.
And max rank = Rank A?

After a quick think, here's some points I hope help
# equations = rows of A = m
# unknowns = columns of A = n

So you have Rank(A) <= min(m,n).
and Rank(A|B) <= min(m,n+1)

Note when you augment A to A|B you effectively add a column vector, so Rank(A|B) >= Rank(A),
 
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  • #5
Lane,
Thank you so much for your reply. Sure enough it was on my exam today (which is killed!)
Was very uncertain about small parts of the rank, but you cleared it up.

Thanks!

Ben
 

FAQ: Linear Algebra : Rank of a matrix

1. What is the rank of a matrix?

The rank of a matrix is the maximum number of linearly independent rows or columns in the matrix. In other words, it is the dimension of the vector space spanned by the rows or columns of the matrix.

2. How is the rank of a matrix calculated?

The rank of a matrix can be calculated by performing row reduction on the matrix and counting the number of non-zero rows in the reduced matrix. Alternatively, the rank can also be found by counting the number of linearly independent rows or columns in the matrix.

3. What does it mean if a matrix has full rank?

If a matrix has full rank, it means that all of its rows and columns are linearly independent. This also means that the matrix is invertible, and its determinant is non-zero.

4. Can the rank of a matrix be greater than its dimensions?

No, the rank of a matrix cannot be greater than its dimensions. The rank of a matrix is always less than or equal to the smaller of its number of rows and columns.

5. How is the rank of a matrix related to its null space and column space?

The rank of a matrix is equal to the dimension of its column space. This means that the number of linearly independent columns in a matrix is equal to its rank. Additionally, the dimension of the null space, or the set of all solutions to the equation Ax=0, is equal to the number of columns minus the rank of the matrix.

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