Adaptive signal processing
Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
New approximations of differential entropy for independent component analysis and projection pursuit
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Extraction of Specific Signals with Temporal Structure
Neural Computation
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Blind source separation techniques based on statistical independence criteria require a large number of data samples to estimate higher-order statistics. Thus, those techniques are not suitable to either on-line adaptive modeling. In this work we developed both an online and a batch algorithms for semi-blind extraction of a desired source signal with temporal structure from linear mixtures . Here, we do not assume that sources are statistically independent but we use an a prioriinformation about the autocorrelation function of primary sources to extract the desired signal. Also, we develop an analytical framework to guarantee convergence of the online algorithm based on second-order statistics. Extensive computer simulations and real data applications confirm the validity and high performance of the proposed algorithms.