Automatic and Computationally Efficient Method for Model Selection in Inertial Sensor Calibration

Abstract

This publication contributes to work in applied statistics, signal processing, model selection, with a focus reflected in its title: Automatic and Computationally Efficient Method for Model Selection in Inertial Sensor Calibration.

Publication
Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015), 2003–2006
Applied Statistics Signal Processing Model Selection
Roberto Molinari
Assistant Professor in Statistics

My research interests include robust statistics, signal processing, model selection and differential privacy.