Digital Signal Processing Reference
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4. V. Cherkassky and F. Mulier, Self-organization as an iterative kernel smoothing
process, Neural Computation, 7, 1165-1177, 1995.
5. T. Kohonen, Self-Organizating Maps, 2nd ed., Berlin: Springer-Verlag, 1997.
6. T. Kohonen, The self-organizing map, Proc. IEEE, 78(9), 1464-1480, Sept. 1990.
7. T. Kohonen, E. Oja, O. Simula, A. Visa, and J. Kangas, Engineering applications
of the self-organizing map, Proc. IEEE, 84(10), 1355-1357, Oct. 1996.
8. S. Amari, Dynamical stability of formation of cortical maps, in Dynamic Interac-
tions in Neural Networks: Models and Data, M.A. Arbib and S. Amari, Eds., New
York: Springer, 1989.
9. W.K. Konen, T. Maurer, and C. von der Malsburg, A fast dynamic link matching
algorithm for invariant pattern recognition, Neural Networks, 7(6/7), 1019-1030,
1994.
10. M. Lades, J.C. Vorbr uggen, J. Buhmann, J. Lange, C.v.d. Malsburg, R.P. W urtz,
and W. Konen, Distortion invarinat object recognition in the dynamic link archi-
tecture, IEEE Trans. Comput., 42(3), 300-311, Mar. 1993.
11.T.Kohonen, The neural phonetic typewriter, IEEE Comput., 21(3), 11-22, Mar.
1988.
12.
A. Gersho and R.M. Gray, Vector Quantization and Signal Compression , Dordrecht:
Kluwer, 1992.
13.
H. Robbins and S. Monro, A stochastic approximation method, Ann. Math. Stat.,
22, 400-407, 1951.
14.
H. Ritter and K. Schulten, Convergence properties of Kohonen's topology con-
serving maps: fluctuations, stability and dimension selection, Biol. Cybern., 60,
59-71, 1989.
15.
T. Kohonen, Analysis of a simple self-organizing process, Biol. Cybern., 44, 135-
140, 1982.
16.
M. Cottrell and J.C. Fort, A stochastic model for retinotopy: a self-organizing
process, Biol. Cybern., 53, 405-411, 1986.
17.
H. Ritter and K. Schulten, On the stationary state of Kohonen's self-organizing
sensory mapping, Biol. Cybern., 54, 99-106, 1986.
18.
V.V. Tolat, An analysis of Kohonen's self-organizing maps using a system of
energy functions, Biol. Cybern., 64, 155-164, 1990.
19.
Z.-P. Lo, Y. Yu, and B. Bavarian, Analysis of the convergence properties of topol-
ogy preserving neural networks, IEEE Trans. Neural Networks, 4(2), 207-220, Mar.
1993.
20.
G. Voronoi, Recherches sur les paralleloedres primitives, J. Reine Angew. Math.,
134, 198-287, 1908.
21.
N.G. Van Kampen, Stochastic Processes in Physics and Chemistry , Amsterdam:
North Holland, 1981.
22.
C.W. Gardiner, Handbook of Stochastic Methods, 2nd ed., Berlin: Springer-Verlag,
1985.
23.
S. Haykin, Adaptive Filter Theory , Englewood Cliffs, NJ: Prentice-Hall, 1986.
24.
C. Kotropoulos, X. Magnisalis, I. Pitas, and M.G. Strintzis, Nonlinear ultrasonic
image processing based on signal-adaptive filters and self-organizing neural
networks, IEEE Trans. Image Process., 3(1), 65-77, Jan. 1994.
25.
M.G. Strintzis, Convergence analysis of variants of the learning vector quantizer,
personal communication.
26.
D.M. Clark and K. Ravishankar, A convergence theorem for Grossberg learning,
Neural Networks, 3, 87-92, 1990.
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