Publicaciones en las que colabora con A. M. Tomé (27)

2016

  1. Functional biomedical images of Alzheimer’s disease. A green’s function-based empirical mode decomposition study

    Current Alzheimer Research, Vol. 13, Núm. 6, pp. 695-707

2015

  1. A logistic non-negative matrix factorization approach to binary data sets

    Multidimensional Systems and Signal Processing, Vol. 26, Núm. 1, pp. 125-143

2014

  1. A new Bayesian approach to nonnegative matrix factorization: Uniqueness and model order selection

    Neurocomputing, Vol. 138, pp. 142-156

  2. Physarum Learner: A bio-inspired way of learning structure from data

    Expert Systems with Applications, Vol. 41, Núm. 11, pp. 5353-5370

2013

  1. Sliding empirical mode decomposition-brain status data analysis and modeling

    Studies in Computational Intelligence, Vol. 410, pp. 311-349

  2. Weighted sliding empirical mode decomposition for online analysis of biomedical time series

    Neural Processing Letters

2012

  1. Brain connectivity analysis: A short survey

    Computational Intelligence and Neuroscience, Vol. 2012

2011

  1. Brain status data analysis by sliding EMD

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Sliding empirical mode decomposition for on-line analysis of biomedical time series

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2010

  1. Brain status data analyzed by empirical mode decomposition

    Proceedings of the International Joint Conference on Neural Networks

  2. Empirical mode decomposition - An introduction

    Proceedings of the International Joint Conference on Neural Networks

  3. Machine learning techniques to identify marker genes for diagnostic classification of microarrays

    Machine Learning Research Progress (Nova Science Publishers, Inc.), pp. 107-176

2009

  1. How to apply nonlinear subspace techniques to univariate biomedical time series

    IEEE Transactions on Instrumentation and Measurement

2008

  1. Hybridizing sparse component analysis with genetic algorithms for microarray analysis

    Neurocomputing, Vol. 71, Núm. 10-12, pp. 2356-2376

  2. ICA analysis of retina images for glaucoma classification

    Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

2007

  1. Blind matrix decomposition techniques to identify marker genes from microarrays

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Blind matrix decomposition via genetic optimization of sparseness and nonnegativity constraints

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Single-channel electroencephalogram analysis using non-linear subspace techniques

    2007 IEEE International Symposium on Intelligent Signal Processing, WISP

  4. Sparse nonnegative matrix factorization with genetic algorithms for microarray analysis

    IEEE International Conference on Neural Networks - Conference Proceedings

2006

  1. Denoising using local projective subspace methods

    Neurocomputing, Vol. 69, Núm. 13-15, pp. 1485-1501