Numerical control of kohonen neural network for scattered data approximation

Numerical Algorithms

Volumn 39, Issue 1-3, 2005, Pages 175-186

  Hoffmann, Miklós ^a  

^a ESZTERHÁZY KÁROLY UNIVERSITY   (Hungary)

Author keywords

B spline surface; Kohonen neural network; Self organizing map; Surface reconstruction

Indexed keywords

EID: 17444380782     PISSN: 10171398     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11075-004-3628-7     Document Type: Article

References (21)

1. J. Barhak and A. Fischer, Parameterization and reconstruction from 3D scattered points based on neural network and PDE techniques, IEEE Trans. Visual. Comput. Graphics 7 (2001) 1-16.
2. J. Barhak and A. Fischer, Adaptive reconstruction of freeform objects with 3D SOM neural network grids, Computers Graphics 26 (2002) 745-751.
3. G. Echevarría, A. Iglesias and A. Gálvez, Extending neural networks for B-spline surface reconstruction, in: Lecture Notes in Computer Science, Vol. 2330 (Springer, New York, 2002) pp. 305-331.
4. J. Freeman and D. Skapura, Neural Networks: Algorithms, Applications and Programming Techniques (Addison-Wesley, Reading, MA, 1991).
5. B. Fritzke, Growing cell structures - a self-organizing network for unsupervised and supervised learning, Neural Networks 7 (1994) 1441-1460.
6. V. Hlavaty, Differential Line Geometry (Nordhoff, Leiden, 1953).
7. M. Hoffmann, Modified Kohonen neural network for surface reconstruction, Publ. Math. 54 (1999) 857-864.
8. M. Hoffmann and L. Várady, Free-form surfaces for scattered data by neural networks, J. Geometry Graphics 2 (1998) 1-6.
9. I.P. Ivrissimtzis, W.-K. Jeong and H.-P. Seidel, Using growing cell structures for surface reconstruction, in: Proc. of the Shape Modeling International'03 (2003) pp. 78-86.
10. I.P. Ivrissimtzis, W.-K. Jeong and H.-P. Seidel, Neural meshes: Statistical learning methods in surface reconstrution, Technical Report of Max-Planck Institut für Math., MPI-I-2003-4-007 (2003).
11. W.-K. Jeong, I.P. Ivrissimtzis and H.-P. Seidel, Neural meshes: Statistical learning based on normals, in: Proc. of Pacific Graphics'03 (IEEE Computer Soc. Press, Los Alamitos, CA, 2003) to appear.
12. G.K. Knopf and A. Sangole, Interpolating scattered data using 2D self-organizing feature maps, Graphical Models 66 (2004) 50-69.
13. T. Kohonen, Self-organization and Associative Memory, 3rd ed. (Springer, Berlin, 1996).
14. F.L. Krause, A. Fischer, N. Gross and J. Barhak, Reconstruction of freeform objects with arbitrary topology using neural networks and subdivision techniques, CIRP Annals - Manufacturing Technology 52 (2003) 125-128.
15. W. Ma and P. He, B-spline surface local updating with unorganized points, Computer-Aided Design 30 (1998) 853-862.
16. L. Piegl and W. Tiller, Parametrization for surface fitting in reverse engineering, Computer-Aided Design 33 (2001) 593-603.
17. R. Rojas, Neural Networks. A Systematic Introduction (Springer, Berlin, 1996).
18. L. Várady, M. Hoffmann and E. Kovács, Improved free-form modelling of scattered data by dynamic neural networks, J. Geometry Graphics 3 (1999) 177-183.
19. T. Várady, R.R. Martin and J. Cox, Reverse engineering of geometric models - an introduction, Computer-Aided Design 29 (1997) 255-268.
20. V. Weiss, L. Andor, G. Renner and T. Várady, Advanced surface fitting techniques, Computer Aided Geom. Design 19 (2002) 19-42.
21. Y. Yu, Surface reconstruction from unorganized points using self-organizing neural networks, in: Proc. of IEEE Visualization 99 (1999) pp. 61-64.