This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Robust Inference for Random Fields and Latent Models.
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Robust Inference for Time Series Models: A Wavelet-Based Framework.
This publication contributes to work in applied statistics, signal processing, model selection, with a focus reflected in its title: An Inertial Sensor Calibration Platform to Estimate and Select Error Models.
This publication contributes to work in applied statistics, signal processing, with a focus reflected in its title: A Computationally Efficient Platform for Inertial Sensor Calibration.
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.
An algorithm based on the Generalized Method of Wavelet Moments (GMWM) is presented for identifying the nature and parameters of stochastic processes in time series, enabling automatic model selection and ranking, with applications demonstrated for low-cost MEMS IMUs
This publication contributes to work in signal processing, with a focus reflected in its title: Beyond Allan Variance-GMWM Framework for Sensor Calibration.
A robust time series estimation method is proposed by enhancing the Generalized Method of Wavelet Moments (GMWM) with a robust M-estimator for Wavelet Variance, demonstrating validity through simulation results.
This publication contributes to work in signal processing, with a focus reflected in its title: Study of MEMS-Based Inertial Sensors Operating in Dynamic Conditions.
This publication contributes to work in applied statistics, signal processing, with a focus reflected in its title: An Algorithm for Automatic Inertial Sensors Calibration.