Computing the Nearest Rank-Deficient Matrix Polynomial
Computing the Nearest Rank-Deficient Matrix Polynomial is a scholarly work, published in 2017. The main subjects of the publication include combinatorics, polynomial matrix, square matrix, mathematical optimization, symmetric matrix, polynomial, matrix, companion matrix, characteristic polynomial, rank, matrix splitting, numerical linear algebra, mathematics, matrix polynomial, Total least squares, and matrix norm. The authors also show that singular matrices at minimal distance are all isolated, and are surrounded by a basin of attraction of non-minimal solutions.