Penrose Inverse of Bidiagonal Matrices

Introduction. For a real m×n matrix A, the Moore–Penrose inverse A+ is the unique n×m matrix that satisfies the following four properties: AAA = A , AAA = A , (A+A)T = AA , (AA+)T = AA (see [1], for example). If A is a square nonsingular matrix, then A+ = A−1. Thus, the Moore–Penrose inversion generalizes ordinary matrix inversion. The idea of matrix generalized inverse was first introduced in 1920 by E. Moore [2], and was later rediscovered by R. Penrose [3]. The Moore–Penrose inverses have numerous applications in least-squares problems, regressive analysis, linear programming and etc. For more information on the generalized inverses see [1] and its extensive bibliography. In this work we consider the problem of the Moore–Penrose inversion of square upper bidiagonal matrices