In , every row sums to one, so is an eigenvector with eigenvalue . The antisymmetric direction gives eigenvalue . A direction orthogonal to both is , and direct multiplication shows that it lies in the kernel of a linear map. Normalizing all three gives the complete systemThey form an orthonormal basis of . The extra zero eigenvalue reflects the one-dimensional kernel of a linear map for this rank-two rectangular matrix. The question's symbols denote the eigenvalues of ; the nonzero singular values of are their square roots, namely and .
Articles by others on the same topic
There are currently no matching articles.