Amari S. (1998). Natural gradient works efficiently in learning Neural Comput. 10

Amari S, Chen TP, Cichocki A. (2000). Nonholonomic orthogonal learning algorithms for blind source separation. Neural computation. 12 [PubMed]

Amari S, Cichocki A. (1998). Adaptive blind signal processing: Neural network approaches Proc IEEE. 86

Amari S, Cichocki A, Zhang LQ. (1999). Natural gradient algorithm for blind separation of over-determined mixtures with additive noise IEEE Signal Processing Letters. 6

Amari S, Yang HH. (1997). Adaptive on-line learning algorithms for blind separation: Maximum entropy and minimum mutual information Neural Comput. 9

Amari SL, Cichocki A, Yang HH. (1996). A new learning algorithm for blind signal separation. Advances in Neural Information Processing Systems.. 8

Bell AJ, Sejnowski TJ. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural computation. 7 [PubMed]

Cao XR, Liu RW. (1996). General approach to blind source separation IEEE Transactions On Signal Processing. 44

Cardoso JF. (1998). Blind source separation: Statistical principles Proc IEEE. 86

Cardoso JF. (1999). High-order contrasts for independent component analysis. Neural computation. 11 [PubMed]

Cardoso JF. (2000). On the stability of source separation algorithms Journal Of VLSI Signal Processing. 26

Cardoso JF, Laheld B. (1996). Equivalent adaptive source separation. IEEE Trans Signal Proc. 44

Cardoso JF, Pham DT. (2001). Blind separation of instantaneous mixtures of nonstationary sources IEEE Trans On Signal Processing. 49

Choi S, Cichocki A, Sabala I, Orsier B, Szupiluk R. (1997). Self-adaptive independent component analysis for sub-gaussian and super-gaussian mixtures with an unknown number of sources and additive noise International Symposium On Nonlinear Theory And Its Applications. 2

Cichocki A, Chen T, Amari S. (1997). Stability Analysis of Learning Algorithms for Blind Source Separation. Neural networks : the official journal of the International Neural Network Society. 10 [PubMed]

Cichocki A, Karhunen J, Vigario R, Kasprzak W. (1999). Neural networks for blind separation with unknown number of sources Neurocomputing. 24

Cichocki A, Unbehauen R, Rummert E. (1994). Robust learning algorithm for blind separation of signals Electronics Letters. 30

Comon P. (1994). Independent component analysis, a new concept? Signal Processing. 36

Cover TM, Thomas JA. (1991). Elements of Information Theory.

Delfosse N, Loubaton P. (1995). Adaptive blind separation of independent sources: A deflation approach Signal Processing. 45

Douglas SC. (2002). Simple algorithms for decorrelation-based blind source separation IEEE Workshop On Neural Networks For Signal Processing. 12

Douglas SC, Mathis H. (2002). On the existence of universal nonlinearities for blind source separation IEEE Trans Signal Processing. 50

Girolami M. (1999). Self-organising neural networks: Independent component analysis and blind source separation.

Golub GH, van_Loan CF. (1996). Matrix computations.

Lewicki MS, Sejnowski TJ. (2000). Learning overcomplete representations. Neural computation. 12 [PubMed]

Liu R, Tong L, Soon VC, Huang YF. (1991). Indeterminacy and identifiability of blind identification IEEE Trans On Circuits And Systems. 38

Moreau E, Macchi O. (1996). High-order contrasts for self-adaptive source separation International Journal Of Adaptive Control And Signal Processi. 10

Moreau E, Thirion-Moreau N. (1999). Nonsymmetrical contrasts for source separation IEEE Trans On Signal Processing. 47

Ohata M, Matsuoka K. (2002). Stability analysis of information-theoretic blind separation algorithms in the case where the sources are nonlinear processes IEEE Trans Signal Processing. 50

Oja E. (1997). The nonlinear PCA learning rule and signal separation: Mathematical analysis Neurocomputing. 17

Oja E, Hyvarinen A. (1997). A fast fixed-point algorithm for independent component analysis Neural Comput. 9

Oja E, Hyvarinen A, Karunen J. (2001). Independent component analysis.

Oja E, Karhunen J, Pajunen P. (1998). The nonlinear PCA criterion in blind source separation: Relations with other approaches Neurocomputing. 22

Pham DT. (2002). Mutual information approach to blind separation of stationary sources IEEE Trans Information Theory. 48

Sherman DA, Pasion SG, Forsburg SL. (1998). Multiple domains of fission yeast Cdc19p (MCM2) are required for its association with the core MCM complex. Molecular biology of the cell. 9 [PubMed]

Wang J, Li YQ. (2002). Sequential blind extraction of instantaneously mixed sources IEEE Trans On Signal Processing. 50

Ye JM, Zhu XL, Zhang XD. (2004). Adaptive Blind Separation with an Unknown Number of Sources Neural Comput. 16

Zhu XL, Zhang XD. (2002). Adaptive RLS algorithm for blind source separation using a natural gradient Ieee Signal Processing Letters. 9

Zhu XL, Zhang XD. (2004). Overdetermined blind source separation based on singular value decomposition J Elect Inf Tech. 26

von_Hoff TP, Lindgren AG, Kaelin AN. (2000). Transpose properties in the stability and performance of the classical adaptive algorithms for blind source separation and deconvolution Signal Processing. 80