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The columns of A span the column space, but they may not form a basis if the column vectors are not linearly independent. Fortunately, elementary row operations do not affect the dependence relations between the column vectors. This makes it possible to use row reduction to find a basis for the column space. For example, consider the matrix
An infinite set of vectors is linearly independent if every nonempty finite subset is linearly independent. Conversely, an infinite set of vectors is linearly dependent if it contains a finite subset that is linearly dependent, or equivalently, if some vector in the set is a linear combination of other vectors in the set.
It follows that Ax 1, Ax 2, …, Ax r are linearly independent. Now, each Ax i is obviously a vector in the column space of A. So, Ax 1, Ax 2, …, Ax r is a set of r linearly independent vectors in the column space of A and, hence, the dimension of the column space of A (i.e., the column rank of A) must be at least as big as r.
1 Examples. Toggle Examples subsection. ... are the columns of matrix then the Gram ... a set of vectors are linearly independent if and only if the Gram determinant ...
From the definition of the parity-check matrix it directly follows the minimum distance of the code is the minimum number d such that every d - 1 columns of a parity-check matrix H are linearly independent while there exist d columns of H that are linearly dependent.
When has linearly independent columns (equivalently, is injective, and thus is invertible), + can be computed as + = (). This particular pseudoinverse is a left inverse , that is, A + A = I {\displaystyle A^{+}A=I} .
In mathematics, more specifically in linear algebra, the spark of a matrix is the smallest integer such that there exists a set of columns in which are linearly dependent. If all the columns are linearly independent, s p a r k ( A ) {\displaystyle \mathrm {spark} (A)} is usually defined to be 1 more than the number of rows.
A feasible solution is basic if-and-only-if the columns of the matrix are linearly independent, where K is the set of indices of the non-zero elements of . [ 1 ] : 45 4.