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Mostrando ítems 1-6 de 6
Artículo
Centroid-Based Clustering with ab-Divergences
(MDPI AG, 2019-02-19)
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. ...
Artículo
EEG Signal Processing in MI-BCI Applications With Improved Covariance Matrix Estimators
(IEEE, 2019)
In brain-computer interfaces (BCIs), the typical models of the EEG observations usually lead to a poor estimation of the trial covariance matrices, given the high non-stationarity of the EEG sources. We propose the application ...
Artículo
Initialization method for speech separation algorithms that work in the time-frequency domain
(Acoustical Society of America, 2010)
This article addresses the problem of the unsupervised separa tion of speech signals in realistic scenarios. An initialization procedure is proposed for independent component analysis (ICA) algorithms that work in the ...
Artículo
EEG signal processing in mi-bci applications with improved covariance matrix estimators
(Institute of Electrical and Electronics Engineers Inc., 2019)
n brain–computer interfaces (BCIs), the typical models of the EEG observations usually lead to a poor estimation of the trial covariance matrices, given the high non-stationarity of the EEG sources. We propose the ...
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 ...
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. ...