Accurate, fast and stable denoising source separation algorithms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3195, Issue , 2004, Pages 65-72

  Valpola, Harri ^a,b   Särelä, Jaakko ^b  

^a UNIVERSITY OF ZURICH   (Switzerland)

^b AALTO UNIVERSITY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

BLIND SOURCE SEPARATION; INDEPENDENT COMPONENT ANALYSIS;

ARTIFICIAL DATA; CONTROLLING STEPS; DE-NOISING; DENOISING SOURCE SEPARATIONS; MAGNETOENCEPHALOGRAMS; SEPARATION ALGORITHMS; SIGNAL VARIANCE;

ALGORITHMS;

EID: 35048892032     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30110-3_9     Document Type: Article

References (6)

1. Särelä, J., Valpola, H.: Denoising source separation. Submitted to a journal (2004) Available at Cogprints http://cogprints.ecs.soton.ac.uk/ archive/00003493/.
2. Hyvärinen, A.: Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. on Neural Networks 10 (1999) 626-634
3. Matsuoka, K., Ohya, M., Kawamoto, M.: A neural net for blind separation of nonstationary signals. Neural Networks 8 (1995) 411-419
4. Schwartz, O., Simoncelli, E.P.: Natural signal statistics and sensory gain control. Nature Neuroscience 4 (2001) 819-825
5. Cardoso, J.F.: High-order contrasts for independent component analysis. Neural computation 11 (1999) 157-192
6. Särelä, J., Valpola, H., Vigaŕio, R., Oja, E.: Dynamical factor analysis of rhythmic magnetoencephalographic activity. In: Proc. Int. Conf. on Independent Component Analysis and Signal Separation (ICA2001), San Diego, USA (2001) 451-456