Abstract
This paper proposes a new interpolation method based on Kohonen self-organizing networks. This method performs very well, combining an accuracy comparable with usual optimal methods (kriging) with a shorter computing time, and is especially efficient when a great amount of data is available. Under some hypothesis similar to those used for kriging, unbiasness and optimality of neural interpolation can be demonstrated. A real world problem is finally considered: building a map of surface-temperature climatology in the Mediterranean Sea. This example emphasizes the abilities of the method.
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David, M., Crozet, D., Robb, J.M.: Automated mapping of the ocean floor using the theory of intrinsic random functions of order k. Marine Geophysical Researches 8 (1986) 49–74
Jourdan, D., Balopoulos, E., Garcia-Fernandez, M.-J., Maillard, C.: Objective Analysis of Temperature and Salinity Historical Data Set over the Mediterranean Basin. OCEANS’98, IEE/OES Ed. (1998) vol. 1, 82–87
Jourdan, D.: Bilan du projet MEDATLAS. Technical report 02P98, Service Hydrographique et Océanographique de la Marine (1998)
Kohonen, T.: Self-organizing maps. Springer-Verlag (1995)
Matheron, G.:The intrinsic random functions and their applications. Advances in Applied Probability 5 (1973) 439–468
Ritter, H., Schulten, K.: On the stationnary state of Kohonen’s self-organizing sensory mapping. Biological Cybernetics54 (1986) 99–106
Ritter, H., Schulten, K.: Convergence properties of Kohonen’s topology conserving maps: Fluctuations, stability, and dimension selection. Biological Cybernetics 60 (1988) 59–71
Sarzeaud, O.: Les réseaux de neurones, contribution à une théorie. Ouest Editions (1994)
Sarzeaud, O., Stéphan, Y., Le Corre, F., Kerleguer, L.: Neural meshing of a geographical space in regard to oceanographic data location. OCEANS’94, Brest, France (1994)
Sarzeaud, O.: Interpolation optimale et assimilation de données par réseaux de Kohonen. Technical report OS/99003 (1999)
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© 2000 Springer-Verlag Berlin Heidelberg
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Sarzeaud, O., Stéphan, Y. (2000). Fast Interpolation Using Kohonen Self-Organizing Neural Networks. In: van Leeuwen, J., Watanabe, O., Hagiya, M., Mosses, P.D., Ito, T. (eds) Theoretical Computer Science: Exploring New Frontiers of Theoretical Informatics. TCS 2000. Lecture Notes in Computer Science, vol 1872. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44929-9_11
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DOI: https://doi.org/10.1007/3-540-44929-9_11
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