Sampling Solutions of Inverse Pseudodifferential Equations

Abstract

The main dilemma of modeling inverse problems is that most of them are illposed. The characteristic of such problems is that the closer the mathematical model describes the ill-posed problem, the worse is the “condition” of the associated computational problem (i.e., the more sensitive to errors). Therefore, the indispensable problem is to bring additional information about the desired solution, compromises, or new outlooks as aids to the resolution of ill-posed problems.