Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
A fast fixed-point algorithm for independent component analysis
Neural Computation
Advanced ICA-based receivers for block fading DS-CDMA channels
Signal Processing
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Complex independent component analysis of frequency-domain electroencephalographic data
Neural Networks - Special issue: Neuroinformatics
Average convergence behavior of the FastICA algorithm for blind source separation
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
A blind source separation technique using second-order statistics
IEEE Transactions on Signal Processing
Blind separation of instantaneous mixture of sources via anindependent component analysis
IEEE Transactions on Signal Processing
Undermodeled equalization: a characterization of stationary pointsfor a family of blind criteria
IEEE Transactions on Signal Processing
Complex random vectors and ICA models: identifiability, uniqueness, and separability
IEEE Transactions on Information Theory
Complex ICA using generalized uncorrelating transform
Signal Processing
IEEE Transactions on Neural Networks
The deflation-based FastICA estimator: statistical analysis revisited
IEEE Transactions on Signal Processing
Complex independent component analysis by entropy bound minimization
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Algorithms for complex ML ICA and their stability analysis using wirtinger calculus
IEEE Transactions on Signal Processing
A new performance index for ICA: properties, computation and asymptotic analysis
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Cramér-Rao bound for circular complex independent component analysis
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
A two-stage Independent Component Analysis-based method for blind detection in CDMA systems
Digital Signal Processing
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We derive new fixed-point algorithms for the blind separation of complex-valued mixtures of independent, noncircularly symmetric, and non-Gaussian source signals. Leveraging recently developed results on the separability of complex-valued signal mixtures, we systematically construct iterative procedures on a kurtosis-based contrast whose evolutionary characteristics are identical to those of the FastICA algorithm of Hyvarinen and Oja in the real-valued mixture case. Thus, our methods inherit the fast convergence properties, computational simplicity, and ease of use of the FastICA algorithm while at the same time extending this class of techniques to complex signal mixtures. For extracting multiple sources, symmetric and asymmetric signal deflation procedures can be employed. Simulations for both noiseless and noisy mixtures indicate that the proposed algorithms have superior finite-sample performance in data-starved scenarios as compared to existing complex ICA methods while performing about as well as the best of these techniques for larger data-record lengths.