Blind source separation via generalized eigenvalue decomposition
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Adaptive blind separation with an unknown number of sources
Neural Computation
Blind source separation via generalized eigenvalue decomposition
The Journal of Machine Learning Research
A unifying model for blind separation of independent sources
Signal Processing
Neural Computation
Tensor-based techniques for the blind separation of DS-CDMA signals
Signal Processing
Oracle estimators for the benchmarking of source separation algorithms
Signal Processing
Building Blocks for Variational Bayesian Learning of Latent Variable Models
The Journal of Machine Learning Research
Separation of instantaneous mixtures of cyclo-stationary sources
Signal Processing
Multiuser channel estimation from higher-order statistical matrix pencil
EURASIP Journal on Applied Signal Processing
Noise cancellation with static mixtures of a nonstationary signal and stationary noise
EURASIP Journal on Applied Signal Processing
Permutation correction in the frequency domain in blind separation of speech mixtures
EURASIP Journal on Applied Signal Processing
gpICA: a novel nonlinear ICA algorithm using geometric linearization
EURASIP Journal on Applied Signal Processing
Dereverberation by using time-variant nature of speech production system
EURASIP Journal on Advances in Signal Processing
A robust model for spatiotemporal dependencies
Neurocomputing
Letters: Gaussian moments for noisy unifying model
Neurocomputing
A fixed-point algorithm for blind source separation with nonlinear autocorrelation
Journal of Computational and Applied Mathematics
Optimal Performance of Second-Order Multidimensional ICA
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
On Optimal Selection of Correlation Matrices for Matrix-Pencil-Based Separation
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Least Square Joint Diagonalization of Matrices under an Intrinsic Scale Constraint
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Improvement of the Initialization of ICA Time-Frequency Algorithms for Speech Separation
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Blind Spectral-GMM Estimation for Underdetermined Instantaneous Audio Source Separation
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Underdetermined Instantaneous Audio Source Separation via Local Gaussian Modeling
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Blind source separation with nonlinear autocorrelation and non-Gaussianity
Journal of Computational and Applied Mathematics
Fast nonlinear autocorrelation algorithm for source separation
Pattern Recognition
Using Wavelets and Independent Component Analysis for Quantization Index Modulation Watermarking
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Non-cancellation multistage kurtosis maximization with prewhitening for blind source separation
EURASIP Journal on Advances in Signal Processing
Blind separation of piecewise stationary non-Gaussian sources
Signal Processing
Blind source separation based on cumulants with time and frequency non-properties
IEEE Transactions on Audio, Speech, and Language Processing
MIMO-AR system identification and blind source separation for GMM-distributed sources
IEEE Transactions on Signal Processing
Underdetermined blind source separation based on subspace representation
IEEE Transactions on Signal Processing
A post nonlinear geometric algorithm for independent component analysis
Digital Signal Processing
A simple overcomplete ICA algorithm by non-orthogonal pair optimizations
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Complexity Pursuit for Unifying Model
Neural Processing Letters
Maximum likelihood blind image separation using nonsymmetrical half-plane Markov random fields
IEEE Transactions on Image Processing
Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
Blind MIMO-AR system identification and source separation with finite-alphabet
IEEE Transactions on Signal Processing
A flexible component model for precision ICA
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Blind separation of cyclostationary sources using joint block approximate diagonalization
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Blind audio source separation using sparsity based criterion for convolutive mixture case
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Blind separation of non-stationary images using Markov models
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Blind separation of mutually correlated sources using precoders
IEEE Transactions on Neural Networks
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
The Journal of Machine Learning Research
QML-based joint diagonalization of positive-definite hermitian matrices
IEEE Transactions on Signal Processing
Glimpsing IVA: a framework for overcomplete/complete/undercomplete convolutive source separation
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on processing reverberant speech: methodologies and applications
IEEE Transactions on Signal Processing
Independent component analysis by entropy bound minimization
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Blind extraction of intermittent sources
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Blind Source Separation Using Quadratic form Innovation
Neural Processing Letters
Audio-visual grouplet: temporal audio-visual interactions for general video concept classification
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Generic blind source separation using second-order local statistics
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Simple LU and QR based non-orthogonal matrix joint diagonalization
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
On the identifiability testing in blind source separation using resampling technique
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Algebraic solutions to complex blind source separation
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Joint block diagonalization algorithms for optimal separation of multidimensional components
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Hybrid linear and nonlinear complexity pursuit for blind source separation
Journal of Computational and Applied Mathematics
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
A parallel dual matrix method for blind signal separation
Neural Computation
Hi-index | 35.71 |
Most source separation algorithms are based on a model of stationary sources. However, it is a simple matter to take advantage of possible nonstationarities of the sources to achieve separation. This paper develops novel approaches in this direction based on the principles of maximum likelihood and minimum mutual information. These principles are exploited by efficient algorithms in both the off-line case (via a new joint diagonalization procedure) and in the on-line case (via a Newton-like procedure). Some experiments showing the good performance of our algorithms and evidencing an interesting feature of our methods are presented: their ability to achieve a kind of super-efficiency. The paper concludes with a discussion contrasting separating methods for non-Gaussian and nonstationary models and emphasizing that, as a matter of fact, “what makes the algorithms work” is-strictly speaking-not the nonstationarity itself but rather the property that each realization of the source signals has a time-varying envelope