Cyclostationarity: half a century of research
Signal Processing
Bibliography on cyclostationarity
Signal Processing
Separation of instantaneous mixtures of cyclo-stationary sources
Signal Processing
Estimation of the symbol rate of linearly modulated sequences of symbols
Signal Processing
Blind source separation based on constant modulus criterion and signal mutual information
Computers and Electrical Engineering
On blind MIMO system identification based on second-order cyclic statistics
Research Letters in Signal Processing
EURASIP Journal on Wireless Communications and Networking - Cognitive Radio and Dynamic Spectrum Sharing Systems
Blind source separation using Wold decomposition and second order statistics
MATH'05 Proceedings of the 7th WSEAS International Conference on Applied Mathematics
Blind Separation of Cyclostationary Signals
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
Heart and lung sound separation using periodic source extraction method
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
A new source extraction algorithm for cyclostationary sources
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 mutually correlated sources using precoders
IEEE Transactions on Neural Networks
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
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This paper studies the blind source separation (BSS) problem with the assumption that the source signals are cyclostationary. Identifiability and separability criteria based on second-order cyclostationary statistics (SOCS) alone are derived. The identifiability condition is used to define an appropriate contrast function. An iterative algorithm (ATH2) is derived to minimize this contrast function. This algorithm separates the sources even when they do not have distinct cycle frequencies