EQUALITY OF ROW AND COLUMN RANK (O'Neil's proof) Is there smt wrong?

In summary, the conversation discusses the equality of row and column rank, with O'Neil's proof being presented. The proof states that the dimension of the column space is at most r, but the person involved in the conversation disagrees and presents a different set of vectors that would make the dimension exactly r. However, it is concluded that there is no contradiction between the two statements and both are true.
  • #1
alexyflemming
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0
EQUALITY OF ROW AND COLUMN RANK (o'Neil's proof) Is there smt wrong?

http://www.mediafire.com/imageview.php?quickkey=znorkrmk3k1otjd&thumb=6

Theorem 7.9: EQUALITY OF ROW AND COLUMN RANK
Proof: Page 210.

It writes:...
so the dimension of this column space is AT MOST r (equal to r if these columns are linearly independent, less than r if they are not)

I THINK THIS IS WRONG. Look at the r vectors:
1 0
0 1
: 0
0 :
BETAr+1,1 BETAr+1,2
:
BETAm1 BETAm2


The first r columns of these r vectors are e1,e2,...er. Hence, they are DEFINITELY LINEARLY INDEPENDENT.
There is no way to obtain 1 in the first coordinate of the first of the r vectors from the remaining r-1 vectors since the 1st coordinate of all of the remaining r-1 vectors are all 0.

Hence, the correct one should be:

so the dimension of this column space is EXACTLY r.

Where am I wrong? or O'neil's is really wrong as I indicated.
 
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  • #2
there is no contradiction between his statement and yours, and in fact both statements are true.
 

FAQ: EQUALITY OF ROW AND COLUMN RANK (O'Neil's proof) Is there smt wrong?

1. What is the concept of equality of row and column rank in O'Neil's proof?

The equality of row and column rank in O'Neil's proof refers to the fact that the number of linearly independent rows in a matrix is equal to the number of linearly independent columns. This is also known as the rank of a matrix, and it is an important concept in linear algebra.

2. Why is the equality of row and column rank important?

The equality of row and column rank is important because it allows us to determine the dimension of the column space and row space of a matrix. It also helps in solving systems of linear equations and finding the inverse of a matrix.

3. What is O'Neil's proof for the equality of row and column rank?

O'Neil's proof for the equality of row and column rank states that if the rank of a matrix is r, then there exists an r × r submatrix with nonzero determinant. This means that the number of linearly independent rows is equal to the number of linearly independent columns, and therefore the row and column rank are equal.

4. Are there any exceptions to the equality of row and column rank in O'Neil's proof?

Yes, there are exceptions to the equality of row and column rank in O'Neil's proof. For example, if a matrix has a row or column of all zeros, then the rank of the matrix will be less than the number of rows or columns, respectively. Additionally, if there are linearly dependent rows or columns in the matrix, then the rank will also be less than the number of rows or columns.

5. What are some real-world applications of the equality of row and column rank?

The equality of row and column rank has many real-world applications. It is used in data analysis, image processing, and machine learning to reduce the dimensionality of data. It is also used in economics and finance to analyze relationships between variables. In addition, it has applications in engineering, physics, and chemistry for solving systems of linear equations and modeling physical systems.

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