Blind separation of hybrid mixture signals

Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University

Volumn 38, Issue 2, 2004, Pages 203-206

  Jia, Peng ^a   Cong, Feng Yu ^a   Shi, Xi Zhi ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Blind source separation (BSS); Hybrid mixing signals; Kernel density estimation

Indexed keywords

PROBABILITY DENSITY FUNCTION; SIGNAL PROCESSING;

HYBRID MIXING SIGNALS; KERNEL DENSITY ESTIMATION; RANDOM VARIABLES; SUB GAUSSIAN SIGNALS; SUPER GAUSSIAN SIGNALS;

BLIND SOURCE SEPARATION;

EID: 2642522273     PISSN: 10062467     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (7)

1. Jutten C, Herault J. Space and time adaptive signal processing by neural network models [A]. Neural Network for Computing, AIP Conf [C]. Snowbird, UT: Proc, 1986, 151: 207-211.
2. Jones M C, Sheather S J. A brief survey of bandwidth selection for density estimation [J]. Journal of the American Statistical Association, 1996, 91(3): 401-407.
3. Jones M C, Marron J S, Sheather S J. Progress in data-based bandwidth selection for kernel density estimation [J]. Computational Statistics, 1996, 11: 337-381.
4. Comon P. Independent components analysis, a new concept? [J]. Signal Processing, 1994, 36: 287-314.
5. Cardoso J F, Laheld B. Equivariant adaptive source separation [J]. IEEE Trans Signal Processing, 1996, 44: 3017-3030.
6. Fukunaga K, Hostetler L D. The estimation of the gradient of a density function, with applications in pattern recognition [J]. IEEE Trans Information Theory, 1975, IT-21(1): 32-40.
7. Amari S, Douglas S, Cichocki A. Multichannel blind deconvolution and equalization using the natural gradient [A]. Proc 1st IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications [C]. Paris, France: IEEE, 1997. 101-104.