References - Biomedical Signal Analysis: Contemporary Methods and Applications - page 402

Thesis, Institute of Biophysics, University of Regensburg, Germany , 2000.
[106]O. Haraldseth, R. Jones, T. Muller, A. Fahlvik, and A. Oksendal. Comparison
of DTPA, BMA and superparamagnetic iron oxide particles as susceptibility
contrast agents for perfusion imaging of regional cerebral ischemia in the rat. J.
Magn. Reson. Imaging , (8):714-717, 1996.
[107]K. Haris, S. N. Efstratiadis, N. Maglaveras, and A. Katsaggelos. Hybrid image
segmentation using watershed and fast region merging. IEEE Trans. Img. Proc. ,
7(12):1684-1699, 1998.
[108]D. Hartl, M. Griese, R. Gruber, D. Reinhardt, D. Schendel, and
S. Krauss-Etschmann. Expression of chemokine receptors ccr5 and cxcr3 on t cells
in bronchoalveolar lavage and peripheral blood in pediatric pulmonary diseases.
Immunobiology , 206(1 - 3):224-225, 2002.
[109]E. J. Hartman, J. D. Keeler, and J. M. Kowalski. Layered neural networks
with Gaussian hidden units as universal approximations. Neural Computation ,
2(2):210-215, 1990.
[110]S. Haykin. Neural Networks . Macmillan College Publishing, 1994.
[111]S. Haykin. Neural networks. Macmillan College Publishing Company , 1994.
[112]J. Herault and C. Jutten. Space or time adaptive signal processing by neural
network models. In J. Denker, editor, Neural Networks for Computing: Proceedings
of the AIP Conference , pages 206-211, New York, 1986. American Institute of
Physics.
[113]J. Hertz, A. Krogh, and R. Palmer. Introduction to the Theory of Neural
Computation . Addison-Wesley Publishing Company, Redwood City, 1991.
[114]H. Herzog. Basic ideas and principles for quantifying regional blood flow with
nuclear medical techniques. Nuklearmedizin , (5):181-185, 1996.
[115]S. Heywang, A. Wolf, and E. Pruss. MRI imaging of the breast: Fast imaging
sequences with and without gd-DTPA. Radiology , 170(2):95-103, 1989.
[116]J. Holland. Adaptation in Natural and Artificial Systems .Universityof
Michigan Press, 1975.
[117]J. Hopfield. Neural networks and physical systems with emergent collective
computational abilities. Proceedings of the National Academy of Science, USA ,
79(8):2554-2558, 1982.
[118]J. Hopfield and D. Tank. Computing with neural circuits: A model. Science ,
233(4764):625-633, 1986.
[119]K. Hornik, M. Stinchcombe, and H. White. Multilayer feedforward networks
are universal approximators. Neural Networks , 2:359-366, 1989.
[120]A. Hyvarinen. Fast and robust fixed-point algorithms for independent
component analysis. IEEE Transactions on Neural Networks , 10(3):626-634, 1999.
[121]A. Hyvarinen and P. Hoyer. Emergence of phase and shift invariant features
by decomposition of natural images into independent feature subspaces. Neural
Computation , 12(7):1705-1720, 2000.
[122]A. Hyvarinen, P. Hoyer, and M. Inki. Topographic independent component
analysis. Neural Computation , 13(7):1525-1558, 2001.
[123]A. Hyvarinen, J. Karhunen, and E. Oja. Independent Component Analysis .
Wiley Interscience, 2001.
[124]A. Hyvarinen and E. Oja. A fast fixed-point algorithm for independent
component analysis. Neural Computation , 9:1483-1492, 1997.
[125]A. Hyvarinen and P. Pajunen. On existence and uniqueness of solutions in
nonlinear independent component analysis. In Proceedings of the 1998 IEEE
International Joint Conference on Neural Networks (IJCNN '98) , vol. 2:1350-1355,