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Minimum classification error training of hidden Markov models for sequential data in the wavelet domain
(Asociación Española para la Inteligencia Artificial, 2009-10)
In the last years there has been increasing interest in developing discriminative training methods for hidden Markov models, with the aim to improve their performance in classification and pattern recognition tasks. Although ...
Estimación de parámetros de modelos a priori para segmentación contextual de imágenes
(2014-02)
En esta tesis se trabaja en el problema de la estimación del parámetro de una familia exponencial de distribuciones de Gibbs, y su relación con el proceso de segmentación contextual de imágenes vía el algoritmo Iterated ...
Density estimation for measurement purposes and convergence improvement using MCMC
(IEEE, 2003-05)
The purpose of this paper is to present a new approach for measurement uncertainty characterization. The Markov Chain Monte Carlo (MCMC) is applied to measurement pdf estimation, which is considered as an inverse problem. ...
Characterization of the statistical behavior of the sediment transport through numerical simulationsCharacterization of the statistical behavior of the sediment transport through numerical simulationsCharacterizatión of the statistical behaviór of the sediment transport through numerical simulatiónscharacterizatión of the statistical behaviór of the sediment transport through numerical simulatións
(2018)
The sediment transport driven by a river or a channel flow is a phenomenon that operates at different scales. At the smallest scales, the coherent structures of the turbulent boundary layer are the mechanisms that govern ...
Bayesian Entropy Estimation: Applications in Robust Image Filtering
(IEEE Electronics, 2012-02)
We introduce a new approach for image filtering in a Bayesian framework, in this case the probability density function (pdf) of the likelihood function is approximated using the concept of non-parametric or kernel estimation. ...
MAP entropy estimation: Applications in robust image filtering
(European Optical Society, 2013-07)
We introduce a new approach for image filtering in a Bayesian framework. In this case the probability density function (pdf) of the likelihood function is approximated using the concept of non-parametric or kernel estimation. ...
New approach of entropy estimation for robust image segmentation
(ROPECIEEE, 2012-11)
In this work we introduce a new approach for robust image segmentation. The idea is to combine two strategies
within a Bayesian framework. The first one is to use a Márkov Random Field (MRF), which allows to introduce ...
Quantum correlations and coherence between two particles interacting with a thermal bath
(IOP Publishing, 2017-05)
Quantum correlations and coherence generated between two free spinless particles in the lattice, interacting with a common quantum phonon bath, are studied. The reduced density matrix is solved using the Markov approach. ...
Billiards in a General Domain with Random Reflections
(SPRINGER, 2009)
We study stochastic billiards on general tables: a particle moves according to its constant velocity inside some domain D R(d) until it hits the boundary and bounces randomly inside, according to some reflection law. We ...