Denoising using local ICA and Kernel-PCA

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 3, Issue , 2004, Pages 2071-2076

  Gruber, P ^a   Theis, F J ^a   Stadlthanner, K ^a   Lang, E W ^a   Tome A M ^b   Teixeira, A R ^b  

^a UNIVERSITY OF REGENSBURG   (Germany)

^b UNIVERSITY OF AVEIRO   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOCORRELATION METHOD; DENOISING ALGORITHMS; FMRI; GAUSSIAN DISTRIBUTION; MINIMUM DESCRIPTION LENGTH (MDL);

ALGORITHMS; BLIND SOURCE SEPARATION; CORRELATION METHODS; EIGENVALUES AND EIGENFUNCTIONS; INDEPENDENT COMPONENT ANALYSIS; NUCLEAR MAGNETIC RESONANCE; PRINCIPAL COMPONENT ANALYSIS; SPURIOUS SIGNAL NOISE; VECTORS; WAVELET TRANSFORMS;

SIGNAL PROCESSING;

EID: 10844278202     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2004.1380936     Document Type: Conference Paper

References (19)

1. Andrzej Cichocki and Shun-Ichi Amari. Adaptive Blind Signal and Image Processing. Wiley, 2002.
2. P. Comon. Independent component analysis - a new concept? Signal Processing, 36:287-314, 1994.
3. A. Effern, K. Lehnertz, T. Schreiber, P. David T. Grunwald, and C.E. Elger. Nonlinear denoising of transient signals with application to event-related potentials. Physica D, 140:257-266, 2000.
4. E. Fishier and H. Messer. On the use of order statistics for improved detection of signals by the MDL criterion. IEEE Transactions on Signal Processing, 48:2242-2247, 2000.
5. J. Hérault and C. Jutten. Space or time adaptive signal processing by neural network models. In J.S. Denker, editor, Neural Networks for Computing. Proceedings of the AIP Conference, pages 206-211, New York, 1986. American Institute of Physics.
6. Aapo Hyvärinen, Patrik Hoyer, and Erkki Oja. Intelligent Signal Processing, chapter Image Denoising by Sparse Code Shrinkage. IEEE Press, 2001.
7. A. Hyvärinen and E. Oja. A fast fixed-point algorithm for independent component analysis. Neural Computation, 9:1483-1492, 1997.
8. A.K. Jain and R.C. Dubes. Algorithms for Clustering Data. Prentice Hall: New Jersey, 1988.
9. A.P. Liavas and P.A. Regalia. On the behavior of information theoretic criteria for model order selection. IEEE Transactions on Signal Processing, 49:1689-1695, 2001.
10. Chor Tin Ma, Zhi Ding, and Sze Fong Yau. A two-stage algorithm for MIMO blind deconvolution of nonstationary colored noise. IEEE Transactions on Signal Processing, 48:1187-1192, 2000.
11. K. Pearson. On lines and planes of closest fit to systems of points in space. Philosophical Magazine, 2:559-572, 1901.
12. K. Stadlthanner, F.J. Theis, E.W. Lang, A.M. Tomé, W. Gronwald, and H.-R. Kalbitzer. A matrix pencil approach to the blind source separation of artifacts in 2D NMR spectra. Neural Information Processing - LR, 1(3): 103-110, 2002.
13. Ana Maria Tomé and Nuno Ferreira. On-line source separation of temporally correlated signals. In European Signal Processing Conference, EUSIPCO2002, Toulouse, France, 2002.
14. Ana Maria Tomé. Blind source separation using a matrix pencil. In Int. Joint Conf. on Neural Networks, Como, Italy, 2000.
15. Ana Maria Tomé. An iterative eigendecomposition approach to blind source separation. In 3rd International Conference on Independent Component Analysis and Signal Separation, pages 424-428, San Diego, USA, 2001.
16. Lang Tong, Ruey-wen Liu, Victor C. Soon, and Yin-Fang Huang. Indeterminacy and identifiability of blind identification. IEEE Transactions on Circuits and Systems, 38(5):499-509, 1991.
17. Rolf Vetter, J.M. Vesin, Patrick Celka, and Jens Krauss Philippe Renevey. Automatic nonlinear noise reduction using local principal component analysis and mdl parameter selection. Proceedings of the IASTED International Conference on Signal Processing Pattern Recognition and Applications (SPPRA 02) Crete, pages 290-294, 2002.
18. Rolf Vetter. Extraction of efficient and characteristic features of multidimensional time series. PhD thesis, EPFL, Lausanne, 1999.
19. P. Vitányi and M. Li. Miminum description length induction, bayesianism, and kolmogorov complexity. IEEE Transactions on Information Theory, 46:446-464, 2000.