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A comprehensive overview of the rank of a matrix, its definition, properties, and methods for computing it using minors and elementary row operations. The document also explains the concept of row-echelon form and how gaussian elimination can be used to transform a matrix into this form. Examples are provided to illustrate the concepts.
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Let A be an m × n - matrix. A minor of order k of A is a determinant of a
k × k sub-matrix of A.
We obtain the minors of order k from A by first deleting m − k rows and
n − k columns, and then computing the determinant. There are usually
many minors of A of a given order.
Example: Find the minors of order 3 of the matrix
Start with the minors of maximal order k. If there is one that is non-zero,
then rank(A) = k. If all maximal minors are zero, then rank(A) < k, and
we continue with the minors of order k1 and so on, until we find a minor
that is non-zero. If all minors of order 1 (i. e. all entries in A) are zero the
rank(A) = 0.
Example: Find the rank of the matrix
rank(A) ≤ min{m, n}
rank(A
T ) = rank(A)
If A is a square matrix of order n then
A is invertible ⇐⇒ det(A) 6 = 0 ⇐⇒ rank(A) = n
The elementary row operation do not change the rank of a matrix.
elementary operations −−−−−−−−−−−→ B (row echelon form)
=⇒ rank(A) = number of non-zero rows of B
Example: Find the rank of matrix A =
=⇒ rank(A) = 3