Second Order Nonstationary Source Separation
Journal of VLSI Signal Processing Systems
An Adaptive Method for Subband Decomposition ICA
Neural Computation
Neural Computation
Kernel Methods for Measuring Independence
The Journal of Machine Learning Research
Distributed Jacobi joint diagonalization on clusters of personal computers
International Journal of Parallel Programming
Separating more sources than sensors using time-frequency distributions
EURASIP Journal on Applied Signal Processing
Blind separation of nonstationary sources based on spatial time-frequency distributions
EURASIP Journal on Applied Signal Processing
Blind sparse source separation using cluster particle swarm optimization technique
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Computational Intelligence and Neuroscience - EEG/MEG Signal Processing
Identification of motor unit discharge patterns in time-frequency plane
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Blind source separation of FM and Doppler signals using T-distributions
ICECS'03 Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing
Astrophysical image separation by blind time--frequency source separation methods
Digital Signal Processing
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
Underdetermined Instantaneous Audio Source Separation via Local Gaussian Modeling
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Underdetermined blind source separation based on relaxed sparsity condition of sources
IEEE Transactions on Signal Processing
Blind source separation based on the array-averaged fractional Fourier transform
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Underdetermined blind separation of non-sparse sources using spatial time-frequency distributions
Digital Signal Processing
Multidimensional Systems and Signal Processing
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
A robust method to count and locate audio sources in a multichannel underdetermined mixture
IEEE Transactions on Signal Processing
Noninvertible gabor transforms
IEEE Transactions on Signal Processing
Blind signal separation and identification of mixtures of images
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
A new blind method for separating M+1 sources from M mixtures
Computers & Mathematics with Applications
QML-based joint diagonalization of positive-definite hermitian matrices
IEEE Transactions on Signal Processing
Anechoic Blind Source Separation Using Wigner Marginals
The Journal of Machine Learning Research
Blind dependent sources separation method using wavelet
International Journal of Computer Applications in Technology
Blind source separation based on power spectral density
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Contrast functions for blind source separation based on time-frequency information-theory
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Information–Theoretic nonstationary source separation
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Convolutive blind separation of non-white broadband signals based on a double-iteration method
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Blind source separation based on high-resolution time-frequency distributions
Computers and Electrical Engineering
Subspace-based technique for speech encryption
Digital Signal Processing
Mixing matrix estimation using discriminative clustering for blind source separation
Digital Signal Processing
One-unit second-order blind identification with reference for short transient signals
Information Sciences: an International Journal
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Blind source separation consists of recovering a set of signals of which only instantaneous linear mixtures are observed. Thus far, this problem has been solved using statistical information available on the source signals. This paper introduces a new blind source separation approach exploiting the difference in the time-frequency (t-f) signatures of the sources to be separated. The approach is based on the diagonalization of a combined set of “spatial t-f distributions”. In contrast to existing techniques, the proposed approach allows the separation of Gaussian sources with identical spectral shape but with different t-f localization properties. The effects of spreading the noise power while localizing the source energy in the t-f domain amounts to increasing the robustness of the proposed approach with respect to noise and, hence, improved performance. Asymptotic performance analysis and numerical simulations are provided