Generalized Gauss Distribution noise model for respiratory parameter estimation

Abstract

In this study, measurement noise is modelled as a Generalized Gauss Distribution and a new method is presented to estimate the model parameters. The estimator algorithm consists of the Kurtosis method, Kalman iterarions and the Maximum likelihood method. The proposed method is successfully applied to linear lung model parameter estimation problem.