Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Adaptive blind separation of independent sources: a deflation approach
Signal Processing
A fast fixed-point algorithm for independent component analysis
Neural Computation
A blind source separation technique using second-order statistics
IEEE Transactions on Signal Processing
Principal independent component analysis
IEEE Transactions on Neural Networks
Single channel speech enhancement by efficient coding
Signal Processing
Letters: Nonlinear innovation to blind source separation
Neurocomputing
An algorithm for extracting fetal electrocardiogram
Neurocomputing
A new constrained fixed-point algorithm for ordering independent components
Journal of Computational and Applied Mathematics
Sequential Blind Signal Extraction with the Linear Predictor
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
On-line Algorithm for Extraction of Specific Signals with Temporal Structure
Neural Information Processing
Nonlinear Innovation to Noisy Blind Source Separation Based on Gaussian Moments
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Journal of Computational and Applied Mathematics
A fixed-point algorithm for blind source separation with nonlinear autocorrelation
Journal of Computational and Applied Mathematics
A Robust and Non-invasive Fetal Electrocardiogram Extraction Algorithm in a Semi-Blind Way
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Blind source separation with nonlinear autocorrelation and non-Gaussianity
Journal of Computational and Applied Mathematics
Fast nonlinear autocorrelation algorithm for source separation
Pattern Recognition
Linear prediction based blind source extraction algorithms in practical applications
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Extraction of gastric electrical response activity from magnetogastrographic recordings by DCA
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Research of blind images separation algorithm based on Kernel space
ICNC'09 Proceedings of the 5th international conference on Natural computation
Noise estimation using mean square cross prediction error for speech enhancement
IEEE Transactions on Circuits and Systems Part I: Regular Papers
QML-based joint diagonalization of positive-definite hermitian matrices
IEEE Transactions on Signal Processing
Extraction of signals with specific temporal structure using kernel methods
IEEE Transactions on Signal Processing
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
Extracting specific signal from post-nonlinear mixture based on maximum negentropy
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Extracting post-nonlinear signal with reference
Computers and Electrical Engineering
A robust extraction algorithm for biomedical signals from noisy mixtures
Frontiers of Computer Science in China
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
A flexible algorithm for extracting periodic signals
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
A two-stage based approach for extracting periodic signals
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Hybrid linear and nonlinear complexity pursuit for blind source separation
Journal of Computational and Applied Mathematics
Harmonic retrieval by period blind source extraction method: Model and algorithm
Digital Signal Processing
Noisy component extraction with reference
Frontiers of Computer Science: Selected Publications from Chinese Universities
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In this work we develop a very simple batch learning algorithm for semiblind extraction of a desired source signal with temporal structure from linear mixtures. Although we use the concept of sequential blind extraction of sources and independent component analysis, we do not carry out the extraction in a completely blind manner; neither do we assume that sources are statistically independent. In fact, we show that the a priori information about the autocorrelation function of primary sources can be used to extract the desired signals (sources of interest) from their linear mixtures. Extensive computer simulations and real data application experiments confirm the validity and high performance of the proposed algorithm.