EEG artifact removal—state-of-the-art and guidelines
JA Urigüen, B Garcia-Zapirain - Journal of neural engineering, 2015 - iopscience.iop.org
This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …
the main sources of interference encountered in the electroencephalogram (EEG) …
Data-driven model reduction and transfer operator approximation
In this review paper, we will present different data-driven dimension reduction techniques for
dynamical systems that are based on transfer operator theory as well as methods to …
dynamical systems that are based on transfer operator theory as well as methods to …
Independent component analysis, a new concept?
P Comon - Signal processing, 1994 - Elsevier
The independent component analysis (ICA) of a random vector consists of searching for a
linear transformation that minimizes the statistical dependence between its components. In …
linear transformation that minimizes the statistical dependence between its components. In …
A blind source separation technique using second-order statistics
Separation of sources consists of recovering a set of signals of which only instantaneous
linear mixtures are observed. In many situations, no a priori information on the mixing matrix …
linear mixtures are observed. In many situations, no a priori information on the mixing matrix …
[CITATION][C] Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
A Cichocki - John Wiley & Sons google schola, 2002 - books.google.com
With solid theoretical foundations and numerous potential applications, Blind Signal
Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume …
Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume …
Blind signal separation: statistical principles
JF Cardoso - Proceedings of the IEEE, 1998 - ieeexplore.ieee.org
Blind signal separation (BSS) and independent component analysis (ICA) are emerging
techniques of array processing and data analysis that aim to recover unobserved signals or" …
techniques of array processing and data analysis that aim to recover unobserved signals or" …
Identification of slow molecular order parameters for Markov model construction
A goal in the kinetic characterization of a macromolecular system is the description of its
slow relaxation processes via (i) identification of the structural changes involved in these …
slow relaxation processes via (i) identification of the structural changes involved in these …
Disentanglement via mechanism sparsity regularization: A new principle for nonlinear ICA
This work introduces a novel principle we call disentanglement via mechanism sparsity
regularization, which can be applied when the latent factors of interest depend sparsely on …
regularization, which can be applied when the latent factors of interest depend sparsely on …
Indeterminacy and identifiability of blind identification
L Tong, RW Liu, VC Soon… - IEEE Transactions on …, 1991 - ieeexplore.ieee.org
Blind identification of source signals is studied from both theoretical and algorithmic aspects.
A mathematical structure is formulated from which the acceptable indeterminacy is …
A mathematical structure is formulated from which the acceptable indeterminacy is …
The cocktail party problem
S Haykin, Z Chen - Neural computation, 2005 - direct.mit.edu
This review presents an overview of a challenging problem in auditory perception, the
cocktail party phenomenon, the delineation of which goes back to a classic paper by Cherry …
cocktail party phenomenon, the delineation of which goes back to a classic paper by Cherry …