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Mostrando ítems 11-19 de 19
Artículo
A Joint Optimization Criterion for Blind DS-CDMA Detection
(Hindawi Publishing Corporation, 2006)
This paper addresses the problem of the blind detection of a desired user in an asynchronous DS-CDMA communications system with multipath propagation channels. Starting from the inverse filter criterion introduced by ...
Artículo
A Sparse-Bayesian Approach for the Design of Robust Digital Predistorters Under Power-Varying Operation
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022)
In this article, a sparse-Bayesian treatment is proposed to solve the crucial questions posed by power amplifier (PA) and digital predistorter (DPD) modeling. To learn a model, the advanced Bayesian framework includes ...
Artículo
Unsupervised Common Spatial Patterns
(Institute of Electrical and Electronics Engineers Inc., 2019)
The common spatial pattern (CSP) method is a dimensionality reduction technique widely used in brain-computer interface (BCI) systems. In the two-class CSP problem, training data are linearly projected onto direc tions ...
Artículo
Optimization of Alpha-Beta Log-Det Divergences and their Application in the Spatial Filtering of Two Class Motor Imagery Movements
(MDPI, 2017-02-25)
The Alpha-Beta Log-Det divergences for positive definite matrices are flexible divergences that are parameterized by two real constants and are able to specialize several relevant classical cases like the squared Riemannian ...
Artículo
Solving permutations in frequencyy-domain for blind separation of an arbitrary number of speech sources
(Acoustical Society of America, 2011)
Blind separation of speech sources in reverberant environ ments is usually performed in the time-frequency domain, which gives rise to the permutation problem: the different ordering of estimated sources for different ...
Tesis Doctoral
Electroencephalograph (EEG) signal processing techniques for motor imagery Brain Computer interface systems
(2018-06-11)
Brain-Computer Interface (BCI) system provides a channel for the brain to control external devices using electrical activities of the brain without using the peripheral nervous system. These BCI systems are being used ...
Artículo
Centroid-Based Clustering with αβ-Divergences
(MDPI AG, 2019)
Centroid-based clustering is a widely used technique within unsupervised learning algorithms in many research fields. The success of any centroid-based clustering relies on the choice of the similarity measure under use. ...
Ponencia
Globally convergent Newton algorithms for blind decorrelation
(2003)
This paper presents novel Newton algorithms for the blind adaptive decorrelation of real and complex processes. They are globally convergent and exhibit an interesting relation ship with the natural gradient algorithm ...
Artículo
Generalized Alpha-Beta Divergences and Their Application to Robust Nonnegative Matrix Factorization
(Multidisciplinary Digital Publishing Institute, 2011)
We propose a class of multiplicative algorithms for Nonnegative Matrix Factorization (NMF) which are robust with respect to noise and outliers. To achieve this, we formulate a new family generalized divergences referred ...