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The challenge of estimating the position, velocity and orientation in space in a precise and reliable way, at any time, with and without reception of satellite signals, is the core subject of this dissertation. To this end, the use of Bayesian filters whic ...
This paper proposes a state estimator for large-scale linear systems described by the interaction of state-coupled subsystems affected by bounded disturbances. We equip each subsystem with a Local State Estimator (LSE) for the reconstruction of the subsyst ...
Alzheimer's disease (AD) disrupts functional connectivity in distributed cortical networks. We analyzed changes in the S-estimator, a measure of multivariate intraregional synchronization, in electroencephalogram (EEG) source space in 15 mild AD patients v ...
We consider goal-oriented a posteriori error estimators for the evaluation of the errors on quantities of interest associated with the solution of geometrically nonlinear curved elastic rods. For the numerical solution of these nonlinear one-dimensional pr ...
The goal of this thesis is to study an anisotropic adaptive algorithm for transonic compressible viscous flow around an airwing. A convection-diffusion model problem is considered, an anisotropic a posteriori error estimator for the H1 semi-norm of the err ...
We propose a novel statistical formulation of the image-reconstruction problem from noisy linear measurements. We derive an extended family of MAP estimators based on the theory of continuous-domain sparse stochastic processes. We highlight the crucial ro ...
We propose a novel statistical formulation of the image-reconstruction problem from noisy linear measurements. We derive an extended family of MAP estimators based on the theory of continuous-domain sparse stochastic processes. We highlight the crucial rol ...
This work is concerned with the estimation of the spreading potential of the disease in the initial stages of an epidemic. A speedy and accurate estimation is important for determining whether or not interventions are necessary to prevent a major outbreak. ...
This paper introduces a new method for QT-interval estimation. It consists in a batch processing mode of the improved Woody's method. Performance of this methodology is evaluated using synthetic data. In parallel, a new model of QT-interval dynamics behavi ...
This paper investigates the use of phoneme class conditional probabilities as features (posterior features) for template-based ASR. Using 75 words and 600 words task-independent and speaker-independent setup on Phonebook database, we investigate the use of ...