Digital Signal Processing Reference
In-Depth Information
second order source separation. In
Proc. ICA 2000
, volume 2, pages 111-116, 2000.
[229]B. Scholkopf and A. Smola.
Learning with Kernels
. MIT Press, Cambridge,
Mass.,, 2002.
[230]H. Schoner, M. Stetter, I. Schießl, J. Mayhew, J. Lund, N. McLoughlin, and
K. Obermayer. Application of blind separation of sources to optical recording of
brain activity. In
Advances in Neural Information Procession Systems
, volume 12,
pages 949-955. MIT Press, 2000.
[231]J. Shi and J. Malik. Normalized cuts and image segmentation.
IEEE Trans.
Pattern Anal. Machine Intell.
, 22(8):888-905, 2000.
[232]W. Siedlecki and J. Sklansky. A note on genetic algorithms for large-scale
feature selection.
Pattern Recognition Letters
, 10(11):335-347, 1989.
[233]V. Skitovitch. On a property of the normal distribution.
DAN SSSR
,
89:217-219, 1953.
[234]V. Skitovitch. Linear forms in independent random variables and the normal
distribution law.
Izvestiia AN SSSR, ser. matem.
, 18:185-200, 1954.
[235]A. Souloumiac. Blind source detection using second order non-stationarity. In
Proc. Int. Conf. Acoustics, Speech and Signal Processing
, pages 1912-1916, 1995.
[236]K. Specht and J. Reul. Function segregation of the temporal lobes into highly
differentiated subsystems for auditory perception: An auditory rapid event-related
fMRI-task.
NeuroImage
, 20:1944-1954, 2003.
[237]K. Stadlthanner, A. Tome, F. Theis, W. Gronwald, H.-R. Kalbitzer, and
E. Lang. Blind source separation of water artifacts in NMR spectra using a matrix
pencil. In
Proc. ICA 2003
, pages 167-172, 2003.
[238]K. Stadlthanner, A. Tome, F. Theis, W. Gronwald, H.-R. Kalbitzer, and
E. Lang. Removing water artefacts from 2D protein NMR spectra using GEVD
with congruent matrix pencils. In
Proc. ISSPA 2003
, volume 2, pages 85-88, 2003.
[239]K. Stadlthanner, A. Tome, F. Theis, and E. Lang. A generalized
eigendecomposition approach using matrix pencils to remove artifacts from 2d
NMR spectra. In
Proc. IWANN 2003
, volume 2687 of
LNCS
, pages 575-582.
Springer, 2003.
[240]G. Stewart. Researches on the circulation time in organs and on the influences
which affect it.
J. Physiol.
, 6:1-89, 1894.
[241]J. Stone, J. Porrill, N. Porter, and I. Wilkinson. Spatiotemporal independent
component analysis of event-related fMRI data using skewed probability density
functions.
NeuroImage
, 15(2):407-421, 2002.
[242]J. Sychra, P. Bandettini, N. Bhattacharya, and Q. Lin. Synthetic images by
subspace transforms I. Principal components images and related filters.
Med.
Phys.
, 21(8):193-201, 1994.
[243]M. Tervaniemi and T. van Zuijen. Methodologies of brain research in cognitive
musicology.
Journal of New Music Research
, 28(3):200-208, 1999.
[244]F. Theis. Nichtlineare ICA mit Musterabstossung. Master's thesis, Institute
of Biophysics, University of Regensburg, Germany, 2000.
[245]F. Theis.
Mathematics in Independent Component Analysis
. Logos Verlag,
Berlin, 2002.
[246]F. Theis. A new concept for separability problems in blind source separation.
Neural Computation
, 16:1827-1850, 2004.
[247]F. Theis. Uniqueness of complex and multidimensional independent
component analysis.
Signal Processing
, 84(5):951-956, 2004.
[248]F. Theis. Uniqueness of real and complex linear independent component
analysis revisited. In
Proc. EUSIPCO 2004
, pages 1705-1708, 2004.
Search WWH ::
Custom Search