Elements of information theory
Elements of information theory
A neural net for blind separation of nonstationary signals
Neural Networks
Joint Approximate Diagonalization of Positive Definite Hermitian Matrices
SIAM Journal on Matrix Analysis and Applications
A blind source separation technique using second-order statistics
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Blind source-separation using second-order cyclostationarystatistics
IEEE Transactions on Signal Processing
Blind separation of instantaneous mixtures of nonstationary sources
IEEE Transactions on Signal Processing
Blind Separation of Cyclostationary Signals
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Optimal Performance of Second-Order Multidimensional ICA
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
IEEE Transactions on Signal Processing
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
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This paper introduces an extension of an earlier method of the author for separating stationary sources, based on the joint approximated diagonalization of interspectral matrices, to the case of cyclostationary sources, to take advantage of their cyclostationarity. the proposed method is based on the joint block approximate diagonlization of cyclic interspectral density. An algorithm for this diagonalization is described. Some simulation experiments are provided, showing the good performance of the method.