Rank of a Matrix and Solving Linear Equations with Vectors

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In summary, the conversation discusses finding the rank of a matrix and solving a system of equations using a specific form. The individual asking the question makes a mistake in calculating the rank and is given a hint to consider the nullity of the matrix. The conversation then continues with the individual attempting to solve the system of equations and asking for guidance on how to incorporate the given form into the solution.
  • #1
rock.freak667
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Homework Statement


Find the rank of the matrix A,where
[tex]A= \left(
\begin{array}{cccc}
1 & 1 & 2 & 3\\
4 & 3 & 5 & 16\\
6 & 6 & 13 & 13\\
14 & 12 & 23 & 45
\end{array}
\right)
[/tex]

Find vectors[tex]x_0[/tex]and[tex]e[/tex] such that any solution of the equation

[tex]Ax= \left(
\begin{array}{c}
0\\
2\\
-1\\
3
\end{array}
\right)
[/tex] [tex](*)[/tex]
can be expressed in the form [tex]x_0+\lambdae[/tex] where [tex]\lambda\epsilonR[/tex]

Hence show that there is no vector which satisfies [tex]*[/tex] and has all its elements positive




Homework Equations



First attempt at such a question, so unknown are any relevant equations

The Attempt at a Solution


Well for the first part to get the rank I put A in RRE form and then counted the number of non-zero rows and got for so [tex]r(A)=4[/tex]

now for the second part,I thought to solve the equation by multiplying by [tex]A^{-1}[/tex] and finding [tex]x[/tex] but then I realized that I have no idea where to get [tex]x_0[/tex] or [tex]\lambda[/tex] or [tex]e[/tex]

can anyone show me how to do these types of questions or can show me some similar example?
 
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  • #2
rock.freak667 said:
Well for the first part to get the rank I put A in RRE form and then counted the number of non-zero rows and got for so [tex]r(A)=4[/tex]
Well, you made a mistake somewhere in here.

You might have guessed that -- if you can write any solution in the form the problem asks for, what does the rank of the matrix have to be?

(Hint: what does the nullity of the matrix have to be?)
 
  • #3
Did I do the row-reduction wrong?
well from wikipedia...[tex]rank(A)+Nullity(A)=n[/tex] well [tex]n=4[/tex] in this case

BTW...This is the first time I have heard of nullity
 
  • #4
rock.freak667 said:
Did I do the row-reduction wrong?
I believe so. The statement of the problem implies the rank is not 4. (In fact, it implies a specific number for the rank) I tried once to do the row reduction myself, and I got the number I expected.
 
  • #5
Well I believe I did it over correctly and got [tex]r(A)=3[/tex]
 
  • #6
yes, you seems to be correct, if this is what you were trying to get:
[tex]\pmatrix{1 & 1 & 2 & 3\cr 0 & 1 & 3 & -4\cr 0 & 0 & 1 & -5\cr 0 & 0 & 0 & 0}[/tex]

use maxima!

http://aycu21.webshots.com/image/27020/2000682090404007350_rs.jpg
 
Last edited:
  • #7
But how do I use the fact that [tex]r(A)=3[/tex] and the nullity to find the vectors in that form?
 
  • #8
Well, how do you normally solve systems of equations? Have you tried that?
 
  • #9
Well normally for that matrix I would just augment it and try to put it in RRE form but then i don't know where [tex]x_0[/tex] and [tex]e[/tex] and [tex]\lambda[/tex] comes in
 
  • #10
Well, try solving it first, then think about it.

By the way, you can edit your original post to fix that one formula; you're supposed to put spaces between things. And it looks a lot nicer if you use [ itex ] instead of [ tex ] for stuff in paragraphs.
 

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. It is a measure of the dimension of the vector space spanned by the rows or columns of the matrix.

2. How is the rank of a matrix determined?

The rank of a matrix can be determined by performing row operations to reduce the matrix to its row echelon form, and then counting the number of non-zero rows. This will give the number of linearly independent rows, which is equal to the rank of the matrix.

3. Can the rank of a matrix be greater than the number of rows or columns?

No, the rank of a matrix cannot be greater than the number of rows or columns. It is always less than or equal to the smaller dimension of the matrix.

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

A matrix has full rank if its rank is equal to the smaller dimension of the matrix. This means that all of its rows and columns are linearly independent, and the matrix is non-singular (has a unique inverse).

5. How is the rank of a matrix related to its determinant?

The rank of a matrix is related to its determinant in that a matrix with full rank (non-singular) has a non-zero determinant. A matrix with less than full rank (singular) will have a determinant of 0.

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