Generalized Tikhonov Regularization for Measurement Data Processing Using Matrix Equations

Abstract

In the measurements practices, mathematical models and processing algorithms are usually formulated in terms of transformations between random vectors. This paper suggests the possibility of employing a novel approach to process measurement data based on transformations between random matrices. Measurements performed on distributed systems constitutes a case of relevant practical interest in which this kind of representation is more suited respect to the traditional vectorial one, since the physical quantities of interest are both space and time sampled. In particular, the proposed approach is applied to the case of indirectly measuring a time varying current density flowing inside a copper conductor