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 …
BSS and ICA in neuroinformatics: from current practices to open challenges
We give a general overview of the use and possible misuse of blind source separation
(BSS) and independent component analysis (ICA) in the context of neuroinformatics data …
(BSS) and independent component analysis (ICA) in the context of neuroinformatics data …
Separation of non-negative mixture of non-negative sources using a Bayesian approach and MCMC sampling
S Moussaoui, D Brie… - IEEE transactions on …, 2006 - ieeexplore.ieee.org
This paper addresses blind-source separation in the case where both the source signals
and the mixing coefficients are non-negative. The problem is referred to as non-negative …
and the mixing coefficients are non-negative. The problem is referred to as non-negative …
[ספר][B] Multivariate Bayesian statistics: models for source separation and signal unmixing
DB Rowe - 2002 - taylorfrancis.com
Of the two primary approaches to the classic source separation problem, only one does not
impose potentially unreasonable model and likelihood constraints: the Bayesian statistical …
impose potentially unreasonable model and likelihood constraints: the Bayesian statistical …
Semi-blind ICA of fMRI: a method for utilizing hypothesis-derived time courses in a spatial ICA analysis
VD Calhoun, T Adali, MC Stevens, KA Kiehl, JJ Pekar - Neuroimage, 2005 - Elsevier
Independent component analysis (ICA) is a data-driven approach utilizing high-order
statistical moments to find maximally independent sources that has found fruitful application …
statistical moments to find maximally independent sources that has found fruitful application …
Comparison of three methods for generating group statistical inferences from independent component analysis of functional magnetic resonance imaging data
VJ Schmithorst, SK Holland - … Imaging: An Official Journal of the …, 2004 - Wiley Online Library
Purpose To evaluate the relative effectiveness of three previously proposed methods of
performing group independent component analysis (ICA) of functional magnetic resonance …
performing group independent component analysis (ICA) of functional magnetic resonance …
A Bayesian approach for blind separation of sparse sources
C Fevotte, SJ Godsill - IEEE Transactions on Audio, Speech …, 2006 - ieeexplore.ieee.org
We present a Bayesian approach for blind separation of linear instantaneous mixtures of
sources having a sparse representation in a given basis. The distributions of the coefficients …
sources having a sparse representation in a given basis. The distributions of the coefficients …
Mean-field approaches to independent component analysis
PAFR Højen-Sørensen, O Winther… - Neural …, 2002 - ieeexplore.ieee.org
We develop mean-field approaches for probabilistic independent component analysis (ICA).
The sources are estimated from the mean of their posterior distribution and the mixing matrix …
The sources are estimated from the mean of their posterior distribution and the mixing matrix …
Spatiotemporal forward solution of the EEG and MEG using network modeling
VK Jirsa, KJ Jantzen, A Fuchs… - IEEE transactions on …, 2002 - ieeexplore.ieee.org
Dynamic systems have proven to be well suited to describe a broad spectrum of human
coordination behavior such as synchronization with auditory stimuli. Simultaneous …
coordination behavior such as synchronization with auditory stimuli. Simultaneous …
Linear-quadratic blind source separation using NMF to unmix urban hyperspectral images
I Meganem, Y Deville, S Hosseini… - IEEE Transactions …, 2014 - ieeexplore.ieee.org
In this work, we propose algorithms to perform Blind Source Separation (BSS) for the linear-
quadratic mixing model. The linear-quadratic model is less studied in the literature than the …
quadratic mixing model. The linear-quadratic model is less studied in the literature than the …