Abstract :
Inversion of the mathematical model is intrinsic to any measurement process, and the numerical complexity of this operation grows with the functional flexibility, accuracy, and speed of measurement. A special case of model inversion, namely, measurement signal reconstruction, is studied, using a linear model of the relationship between two scalar signals. Being numerically ill-conditioned, the reconstruction requires regularization, and reconstruction are classified into six groups according to the mechanism of regularization on which they are based. The six groups are: direct, variational, probabilistic, iterative, parametric, and transform methods
Keywords :
measurement theory; signal processing; direct; iterative; linear model; mathematical model; measurement signal reconstruction; model inversion; numerical complexity; parametric; probabilistic; scalar signals; transform methods; variational; Area measurement; Electric variables measurement; Image reconstruction; Image restoration; Mathematical model; Process control; Seismic measurements; Signal analysis; Signal reconstruction; Signal restoration;
