A noise estimation method for corrupted correlated data

Abstract.

Data acquisition, both in time and in spatial domains, in many cases yields observations with a measurement error. The identification of such a component, that masks the phenomenon under study (signal), must be carried out before the model of interest is specified. The objective of the paper is to propose an estimator for the parameters of an additive noise and compare it with existing methods by applications to both simulated and real data sets.