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Filtering of discrete-time Markov jump linear systems with uncertain transition probabilities
(Wiley-blackwellMaldenEUA, 2011)
Novas propostas em filtragem de projeções tomográficas sob ruído Poisson
(Universidade Federal de São CarlosBRUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCC, 2010-05-24)
In this dissertation we present techniques for filtering of tomographic projections with Poisson noise. For the filtering of the tomogram projections we use variations of three filtering techniques: Bayesian estimation, ...
Early online detection of high volatility clusters using Particle Filters
(Elsevier, 2016-07)
This work presents a novel online early detector of high-volatility clusters based on uGARCH models (a variation of the GARCH model), risk-sensitive particle-filtering-based estimators, and hypothesis testing procedures. ...
Particle-filtering-based failure prognosis via sigma-points: Application to Lithium-Ion battery State-of-Charge monitoring
(Elsevier, 2017)
This paper presents a novel prognostic method that allows a proper characterization of
the uncertainty associated with the evolution in time of nonlinear dynamical systems. The
method assumes a state-space representation ...
Non linear sigma point kalman filter applied to orbit determination using GPS measurements
(2009-01-01)
The purpose of this paper is to present a development of a non linear Kalman filter, based on the sigma point unscented transformation, aiming at real time satellite orbit determination using actual GPS measurements. If ...
Implementation of some Bayesian Filters for structural system identification
(Universidad Nacional de ColombiaManizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - Ingeniería CivilDepartamento de Ingeniería CivilFacultad de Ingeniería y ArquitecturaManizales, ColombiaUniversidad Nacional de Colombia - Sede Manizales, 2018-12)
The present study deals with three different methods for structural identification: the Kalman filter, the Unscented Kalman filter and the Particle filter. The Kalman filter is a known filter for state estimation in linear ...
Neural Collaborative Filtering Classification Model to Obtain Prediction Reliabilities
Neural collaborative filtering is the state of art field in the recommender systems area; it provides some models that obtain accurate predictions and recommendations. These models are regression-based, and they just
return ...
A controlled evaluation of filter paper use during staining of sputum smears for tuberculosis microscopy.
(F1000 Research, 2023)
Background: Some sputum smear microscopy protocols recommend placing filter paper over sputum smears during staining for Mycobacterium tuberculosis (TB) . We found no published evidence assessing whether this is beneficial. ...