The Basic Principles for Stable Approximations to Orthogonal Generalized Inverses of Linear Operators in Hilbert Spaces
Nailin Du · Numerical Functional Analysis and Optimization · 2005
This work presents some basic principles concerned with two general settings for stable approximating orthogonal generalized inverses in Hilbert spaces. In these two settings, perfect convergence and perfect uniform convergence are two important concepts for making theoretical or numerical analysis. Our basic principles characterize the two important concepts by some necessary conditions: stability with other compensated conditions. These basic principles include as simple corollaries some well-known results.