University of Regensburg-ko ikertzaileekin lankidetzan egindako argitalpenak (70)

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

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. Bilateral symmetry aspects in computer-aided Alzheimer's disease diagnosis by single-photon emission-computed tomography imaging

    Artificial Intelligence in Medicine, Vol. 56, Núm. 3, pp. 191-198

  2. 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. Improved likelihood ratio test based voice activity detector applied to speech recognition

    Speech Communication, Vol. 52, Núm. 7-8, pp. 664-677

  4. 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. Automatic selection of ROIs in functional imaging using Gaussian mixture models

    Neuroscience Letters, Vol. 460, Núm. 2, pp. 108-111

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

    IEEE Transactions on Instrumentation and Measurement

  3. Speech enhancement in discontinuous transmission systems using the constrained-stability least-mean-squares algorithm

    Journal of the Acoustical Society of America, Vol. 124, Núm. 6, pp. 3669-3683

  4. fMRI data analysis using a novel clustering technique

    IEEE Nuclear Science Symposium Conference Record

2008

  1. A trade-off between convergence speed and misadjustment for filtering discontinuous speech signals

    European Signal Processing Conference

  2. Automatic computer aided diagnosis tool using component-based SVM

    IEEE Nuclear Science Symposium Conference Record

  3. Clustering approach for the classificarion of SPECT images

    IEEE Nuclear Science Symposium Conference Record