Blind separation of binary sources with less sensors than sources

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 3, Issue , 1997, Pages 1994-1997

  Pajunen, P ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

BEST MATCHING UNITS; BINARY SOURCES; BLIND SEPARATION; COMPETITIVE LEARNING; NEURAL LEARNING; RESEARCH TOPICS; SEPARATION ALGORITHMS; STATISTICAL SIGNAL PROCESSING;

ALGORITHMS; NEURAL NETWORKS; SENSORS; SIGNAL PROCESSING; LEARNING ALGORITHMS; MATHEMATICAL MODELS; MATRIX ALGEBRA; STATISTICAL METHODS; VECTORS;

BLIND SOURCE SEPARATION; LEARNING SYSTEMS;

BLIND SOURCE SEPARATION (BSS);

EID: 0030659997     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.614205     Document Type: Conference Paper

References (5)

1. J. Karhunen, "Neural approaches to independent component analysis and source separation," in Proc. of the J,th European Symposium on Artificial Neural Networks (ESANN'96), (Bruges, Belgium), pp. 249-266, April 1996.
2. J. Proakis, Digital Communications. McGraw-Hill, 3rd ed., 1995.
3. C. Puntonet, A. Prieto, C. Jutten, M. Rodriguez-Alvarez, and J. Ortega, "Separation of sources: A geometry-based procedure for reconstruction of n-valued signals," Signal Processing, vol. 46, pp. 267-284, 1995.
4. M. Herrmann and H. Yang, "Perspectives and limitations of self-organizing maps in blind separation of sources," in Progress in Neural Information Processing (ICONIP-96) (S. Amari et ai, eds.), Springer, 1996.
5. A. Belouchrani and J.-F. Cardoso, "Maximum likelihood source separation by the expectation-maximization technique: Deterministic and stochastic implementation," in Proc. of the 1995 Int. Symposium on Nonlinear Theory and its Applications (NOLTA'95), (Las Vegas, USA), pp. 49-53, December 1995.