This paper presents a new application of independent component analysis mixture modeling (ICAMM) for prediction of electroencephalographic (EEG) signals. Demonstrations in prediction of missing EEG data in a working memory ...
[EN] This paper presents a novel method that combines coupled hidden Markov models (HMM) and non Gaussian mixture models based on independent component analyzer mixture models (ICAMM). The proposed method models the joint ...
[EN] Alpha integration methods have been used for integrating stochastic
models and fusion in the context of detection (binary classification). Our work proposes separated score integration (SSI), a new method based on ...
[EN] Decision fusion consists in the combination of the outputs of multiple classifiers into a common decision that is more precise or stable. In most cases, however, only classical fusion techniques are considered. This ...
Safont Armero, Gonzalo(Universitat Politècnica de València, 2015-07-29)
[EN] This thesis considers new applications of non-Gaussian mixtures in the framework of statistical signal processing and pattern recognition. The non-Gaussian mixtures were implemented by mixtures of independent component ...
[EN] Independent Component Analyzers Mixture Models (ICAMM) are versatile and general models for a large variety of probability density functions. In this paper we assume ICAMM to derive new MAP and LMSE estimators. The ...
[EN] This paper presents a new algorithm for nonlinear prediction based on independent component analysis mixture modelling (ICAMM). The data are considered from several mutually-exclusive classes which are generated by ...
Missing traces in ground penetrating radar (GPR) B-scans (radargrams) may appear because of limited scanning resolution, failures during the acquisition process or the lack of accessibility to some areas under test. Four ...
[EN] Independence between detectors is normally assumed in order to simplify the algorithms and techniques used in decision fusion. In this paper, we derive the optimum fusion rule of N non-independent detectors in terms ...
García Mollá, Víctor Manuel; Salazar Afanador, Addisson; Safont Armero, Gonzalo; Vidal, Antonio M.; Vergara Domínguez, Luís(Springer, 2019-06-14)
In this paper, we present the optimization and parallelization of a state-of-the-art algorithm for automatic classification, in order to perform real-time classification of clinical data. The parallelization has been carried ...
[EN] This paper presents a novel application of pattern recognition to the provenance classification of archae- ological ceramics. This is a challenging problem for archaeologists, which involves assigning a making location ...
Safont Armero, Gonzalo; Salazar Afanador, Addisson; Vergara Domínguez, Luís; Gomez, Enriqueta; Villanueva, Vicente(Institute of Electrical and Electronics Engineers, 2018)
[EN] Independent component analysis (ICA) is a blind source separation technique where data are modeled as linear combinations of several independent non-Gaussian sources. The independence and linear restrictions are relaxed ...
[EN] This paper presents a prospective analysis of non destructive testing (NDT) based on
ultrasounds in the field of archaeology applications. Classical applications of ultrasounds techniques are reviewed, ...
[EN] The detection and identification of internal defects in a material require the
use of some technology that translates the hidden interior damages into observable signals
with different signature-defect correspondences. ...
Xu, Yazhuo(Universitat Politècnica de València, 2019-08-01)
[ES] Este proyecto implementa varias técnicas para la fusión de diferentes modalidades de datos en análisis de las fases del sueño. Los métodos de fusión buscan explotar las complementariedades de los datos para mejorar ...
[EN] Alpha integration is a family of integrators that encompasses many classic fusion operators (e.g., mean, product, minimum, maximum) as particular cases. This paper proposes vector score integration (VSI), a new alpha ...