［1］BELL A J,SEJNOWSKI T J.An information-maximization approach to blind separation and blind deconvolution［J］.Neural Computing,1995(7):1129-1159.

［2］KARHUNEN J,JOUTSENSALO J.Representation and separation of signals using nonlinear PCA type learning［J］.Neural Networks,1994(7):113-127.

［3］KARHUNEN J,PAJUNEN P,OJA E.The nonlinear PCA criterion in blind source separation:Relation with other approaches［J］.Neural Computing,1998(22):5-20.

［4］COMON P.Independent computing analysis,a new concept［J］.Single Processing,1994(36):287-314.

［5］CARDOSO J F,LAHELD B.Equivariant adaptive source separation［J］.IEEE Trans Siganl Processing,1996,44(3):3017-3030.

［6］YANG H H,AMARI S.Adaptive on-line learning algorithms for blind separation—maximum entropy and minimum mutual information［J］.Neural Computation,1997(9):1457-1482

［7］YANG H H.Serial updating rule for blind separation derived from the method of scoring［J］.IEEE Trans Signal Processing,1999,47(5):2279-2285.

［8］CRUCES S,CICHOCKI A,YANG H H.A new learning algorithm for blind signal separation［M］.MA:MIT Press,1996.

［9］AMARI S.Natural gradient works efficiently in learning［J］.Neural Computations,1998(10):251-276.

［10］CRUCES S,CICHOCKI A,CASTEDO L.An iterative inversion approach to blind sources separation［J］.IEEE Trans Neural Networks,2000(11):1423-1437.

［11］MATHEWS V J,XIE Z.A stochastic gradient adaptive filter with gradient adaptive step size［J］.IEEE Trans Signal Processing,1993(41):2075-2087.

［12］ZHANG Xianda,ZHU Xiaolong,BAO Zheng.Grading learning for blind source separation［J］.Science in China:Series F,2003,46(1):31-44.