The column rank of a matrix is the dimension of its image of a linear map, equivalently the dimension of the linear span of its columns. Multiplication on the left by an invertible matrix preserves all column linear relations, and elementary column operations preserve their linear span. In row echelon form the pivot columns form a basis of the column space. Its dimension equals the number of nonzero rows, and hence the row rank.
A pivot column of a matrix is a column whose position contains a leading nonzero matrix entry in its row echelon form. The corresponding columns of the original matrix form a basis of its column space. The column positions survive row operations, although the column vectors themselves generally change.[ref]
Articles by others on the same topic
There are currently no matching articles.