Choi S, Cichocki S, Park H M, Lee S Y. Blind source separation and independent component analysis: a review. Neural Information Processing-Letters and Reviews, 2005, 6(1): 1-57
[2]
Tang Ying, Li Jian-Ping. A new algorithm of ICA: using the parameterized orthogonal matrixes of any dimensions. Acta Automatica Sinica, 2008, 34(1): 31-39(in Chinese)
[3]
Ashi H A, Cummings L J, Matthews P C. Comparison of methods for evaluating functions of a matrix exponential. Applied Numerical Mathematics, 2009, 59(3-4): 468-486
[4]
Fiori S. Quasi-geodesic neural learning algorithms over the orthogonal group: a tutorial. Journal of Machine Learning Research, 2005, 6: 743-781
[5]
Nishimori Y, Akaho S. Learning algorithms utilizing quasi-geodesic flows on the stiefel manifold. Neurocomputing, 2005, 67: 106-135
[6]
Gallier J, Xu D. Computing exponentials of skew-symmetric matrices and logarithms of orthogonal matrices. International Journal of Robotics and Automation, 2002, 17(4): 10-20
[7]
Politi T. A formula for the exponential of a real skew-symmetric matrix of order 4. Bit Numerical Mathematics, 2001, 41(4): 842-845
[8]
Xu L. One-bit-matching theorem for ICA, convex-concave programming on polyhedral set, and distribution approximation for combinatorics. Neural Computation, 2007, 19(2): 546-569
[9]
Shen H, Kleinsteuber M, Huper K. Local convergence analysis of fastICA and related algorithms. IEEE Transactions on Neural Networks, 2008, 19(6): 1022-1032
[10]
Gloub G H, Loan C F V. Matrix Computation (Third Edition). Baltimore: The John Hopkins University Press, 1996. 341-342
[11]
Xiao Ming, Xie Sheng-Li, Fu Yu-Li. Underdetermined blind source separation algorithm based on normal vector of hyperplane. Acta Automatica Sinica, 2008, 34(2): 142-149(in Chinese)
[12]
Bell A J, Sejnowski T J. An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 1995, 7(6): 1129-1159
[13]
Abrudan T E, Eriksson J, Koivunen V. Steepest descent algorithms for optimization under unitary matrix constraint. IEEE Transactions on Signal Processing, 2008, 56(3): 1134-1147
[14]
Fiori S, Tanaka T. An algorithm to compute averages on matrix lie groups. IEEE Transactions on Signal Processing, 2009, 57(12): 4734-4743
[15]
Plumbley M D. Algorithms for nonnegative independent component analysis. IEEE Transactions on Neural Networks, 2003, 14(3): 534-543
[16]
Moakher M. Means and averaging in the group of rotations. SIAM Journal on Matrix Analysis and Applications, 2002, 24(1): 1-16
[17]
Pham D T, Garrat P. Blind separation of mixture of independent sources through a quasi-maximum likelihood approach. IEEE Transactions on Signal Processing, 1997, 45(7): 1712-1725
[18]
Lee T W, Girolami M, Sejnowski T J. Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources. Neural Computation, 1999, 11(2): 417-441
