[2] [2] LO Y K, CHIU H J, SONG T H, et al. A software based CM and DM measurement system for conducted EMI［J］. IEEE Transactions on Industry Electronics Society, 2000, 47(4): 977-978.

[4] [4] FIORI S, BURRASCANO P. Blind electromagnetic source separation and localization［C］//IEEE International Symposium on Circuits and Systems, 2002: 685-688.

[5] [5] MASUGI M, HIRASAWA N, KOBAYASHI R, et al. Proposal of a novel EMI diagnostic system using independent component analysis［C］//The 20th International Zurich Symposium on Electromagnetic Compatibility, 2009: 417-420.

[6] [6] SONG Z F, SU D L, XIE S G. Detecting the number of EMI sources based on higher order statistics［C］//The 20th International Zurich Symposium on Electromagnetic Compatibility, 2009: 465-468.

[10] [10] BELL A J, SEJNOWSKI T J. An information-maximization approach to blind separation and blind deconvolution［J］. Neural Computation, 1995, 7: 1129-1159.

[11] [11] LEE T W, GIROLAMI M, SEJNOWSKI T J. Independent component analysis using an extended infomax algorithm for mixed sub-Gaussian and super-Gaussian sources［J］. Neural Computation, 1999, 11(1): 417-441.

[12] [12] CARDOSO J F, LAHELD B H. Equivariant adaptive source separation［J］. IEEE Transactions on Signal Processing, 1996, 44(12): 3017-3030.

[13] [13] HVVARINEN A. A fast fixed-point algorithm for independent component analysis［J］. Neural Computation, 1997, 9(7): 1483-1492.

[14] [14] BELOUCHRANI A, ABED-MERAIM K, CARDOSO J F, et al. A blind source separation technique using second-order statistics［J］. IEEE Transactions on Signal Processing, 1997, 45(2): 434-444.

[15] [15] AMARI S, CICHOCKI A, YANG H H. A new learning algorithm for blind source separation［J］. Neural Information Processing Systems, 1996, 8: 757-763.