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Stochastic volatility in mean models with scale mixtures of normal distributions and correlated errors: A Bayesian approach
(Elsevier Science BvAmsterdamHolanda, 2011)
Stochastic volatility in mean models with heavy-tailed distributions
(Brazilian Statistical AssociationSao PauloBrasil, 2012)
Estimating model-error covariances in nonlinear state-space models using Kalman smoothing and the expectation-maximization algorithm
(Wiley, 2017-04)
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximization (EM) algorithm to estimate the model-error covariances using ...
Modeling high frequency intraday discrete returns
(2020-04-24)
Esta tese inclui três artigos sobre o tópico de modelagem de retornos intradiários discretos em alta-frequencia. Em todos os artigos nós conduzimos a tarefa de modelar a distribuição condicional discreta das mudanças de ...
Avanços recentes em caracterização e classificação de imagens de texturas: explorando teoria da informação, aprendizado profundo e de variedades
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCCCâmpus São Carlos, 2020-04-30)
The task of extracting features from images is a very important activity for many computer vision and image processing applications. Especially the characterization and identification of textures is a fundamental issue in ...
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 ...
Inuência do número de partículas na estimação de parâmetros via máxima verossimilhança em modelos de espaço de estados
(Universidade Federal de Minas GeraisUFMG, 2018-03-09)
State space models are widely used to model various problems in the areas of economics and biology, so inferences, such as parameter estimation, for this class of models are important. For these cases, the algorithms of ...
Rao-blackwellized particle filter for the cbers-4 attitude and gyros bias estimation
(2020-01-01)
The Rao-Blackwellized particle Filter (RaoBPF) and the Unscented Kalman Filter (UKF) were developed in this work to attitude and gyros bias estimation using simulated orbit and attitude measurement data for CBERS-4 (China ...
Rao-Blackwellized Particle Filter for the CBERS-4 attitude and gyros bias estimation
(2022-04-01)
The Rao-Blackwellized Particle Filter (RaoBPF) and the Unscented Kalman Filter (UKF) were applied in this work to attitude and gyros bias estimation using simulated orbit and attitude measurement data for CBERS-4 (China ...
Control de vibraciones sísmicas y eólicas en una estructura esbelta
(Universidad Michoacana de San Nicolás de Hidalgo, 2020-03)
This work focuses on the control of earthquake and wind vibrations of a reinforced concrete chimney 80 m high, on the Mexican Pacific coast. For the analysis of the chimney, five elastic models and five models that include ...