References - Biomedical Signal Analysis: Contemporary Methods and Applications - page 403

1998.
[126]A. Ilin. Independent dynamics subspace analysis. In Proc. ESANN 2006 ,
pages 345-350, 2006.
[127]C. Jutten, J. Herault, P. Comon, and E. Sorouchiary. Blind separation of
sources, parts I, II and III. Signal Processing , 24:1-29, 1991.
[128]A. Kagan, Y. Linnik, and C. Rao. Characterization Problems in Mathematical
Statistics . Wiley, New York, 1973.
[129]S. Karako-Eilon, A. Yeredor, and D. Mendlovic. Blind Source Separation
Based on the Fractional Fourier Transform. In Proc. ICA 2003 , pages 615-620,
2003.
[130]N. Karayiannis. A methodology for constructing fuzzy algorithms for learning
vector quantization. IEEE Transactions on Neural Networks , 8(3):505-518, 1997.
[131]N. Karayiannis and P. Pai. Fuzzy algorithms for learning vector quantization.
IEEE Transactions on Neural Networks , 7(5):1196-1211, 1996.
[132]J. Karhunen and S. Malaroiu. Local independent component analysis using
clustering. In Proc. First Int. Workshop on Independent Component Analysis and
Blind Signal Separation(ICA99) , pages 43-49, 1999.
[133]J. Karvanen and F. Theis. Spatial ICA of fMRI data in time windows. In
Proc. MaxEnt 2004 , volume 735 of AIP Conference Proceedings , pages 312-319,
2004.
[134]I. Keck, F. Theis, P. Gruber, E. Lang, K. Specht, G. Fink, A. Tome, and
C. Puntonet. Automated clustering of ICA results for fMRI data analysis. In
Proc. CIMED 2005 , pages 211-216, Lisbon, Portugal, 2005.
[135]I. Keck, F. Theis, P. Gruber, E. Lang, K. Specht, and C. Puntonet. 3D spatial
analysis of fMRI data on a word perception task. In Proc. ICA 2004 , volume 3195
of LNCS , pages 977-984. Springer, 2004.
[136]G. Kempermann, H. Kuhn, and F. Gage. More hippocampal neurons in adult
mice living in an enriched environment. Nature , 386(6624):493-495, 1997.
[137]R. Kennan, J. Zhong, and J. Gore. Intravascular susceptibility contrast
mechanism in tissues. Magn. Reson. Med. , pages 9-21, 6 1994.
[138]D. J. Kim, Y. W. Park, and D. J. Park. A novel validity index for
determination of the optimal number of clusters. IEICE Transactions on Inf. and
Syst. , E84-D(2):281-285, 2001.
[139]T. Kohonen. Self-organized formation of topologically correct feature maps.
Biological Cybernetics , 43(1):59-69, 1982.
[140]T. Kohonen. Self-organized formation of topologically correct feature maps.
Biol. Cybern. , 43:59-69, 1982.
[141]T. Kohonen. Self-Organization and Associative Memory . Springer Verlag,
1988.
[142]T. Kohonen, J. Hynninen, J. Kangas, and J. Laaksonen. Som pak: The
self-organizing map program package. Helsinki University of Technology, Technical
Report A31 , 1996.
[143]B. Kosko. Adaptive bidirectional associative memory. Applied Optics ,
26(9):4947-4960, 1987.
[144]C. Kotropoulos, X. Magnisalis, I. Pitas, and M. Strintzis. Nonlinear ultrasonic
image processing based on signal-adaptive filters and self-organizing neural
networks. IEEE Transaction on Image Processing , 3(1):65-77, 1994.
[145]C. K. Kuhl, P. Mielcareck, S. Klaschik, C. Leutner, E. Wardelmann,
J. Gieseke, and H. Schild. Dynamic breast MR imaging: Are signal intensity time
course data useful for differential diagnosis of enhancing lesions? Radiology ,