Apply part (b) to the first column of , using the identity if it is already the zero vector. This gives an orthogonal matrix for which has zeros below its first diagonal entry. At stage , apply a Householder transformation to rows of column , and extend it by the identity on the first coordinates. If that trailing column is zero, again use the identity. The transformation preserves zeros in earlier columns, since their trailing entries already vanish.
After at most stages,is an upper triangular matrix. Each is symmetric and orthogonal, so withwe have andNo invertibility assumption was used, so the Householder QR decomposition also exists for singular matrices.
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