Abstract
Practical implementations of SOM model require parallel and synchronous operation of the network during each iteration in the training stage. However this implicitly implies existence of some communication link between the winner neuron and all other neurons so that update can be induced to the neighboring neurons. In the current paper we report the results of an empirical study on the retention of topology preservation property of the SOM when such links become partially absent, so that during a training iteration not all the neighbors of the winner may be updated. We quantify our results using three different indexes for topology preservation.
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References
Kohonen, T.: The self-organizing map. Proc. IEEE 78(9), 1464–1480 (1990)
Kohonen, T.: Self-Organization and Associative Memory. Springer, Heidelberg (1989)
Anderson, J.A., Pellionisz, A.: Neurocomputing 2: Directions for Research. MIT Press, Cambridge (1990)
E. I. Knudsen, S. Du Lac and S. D. Esterly, “Computational maps in brain”, Ann. Rev. Neurosci., vol. 10, pp. 41-65, 1987.
Kohonen, T.: Automatic formation of topological maps of patterns in a selforganizing sysyem. In: Proc. 2nd Scandinavian Conf. on Image Analysis, pp. 214–220 (1981)
Kohonen, T.: Self-organized formation of topologically correct feature maps. Biol. Cybern. 43, 59–69 (1982)
Bauer, H., Pawelzik, K.R.: Quantifying the Neighborhood Preservation of Self- Organizing Feature Maps. IEEE Trans. on Neural Networks 3(4), 570–579 (1992)
Su, M.C., Chang, H.T., Chou, C.H.: A novel measure for quantifying the topology preservation of self-organizing feature maps. Neural Processing Letters 15(2), 137–145 (2002)
Laha, A., Pal, N.R.: On different variants of self-organizing feature map and their property. In: Proc. of the IEEE Hong Kong Symposium on Robotics and Controls, vol. 1, pp. I344–I349 (1999)
Kendall, M., Gibbons, J.D.: Rank Correlation Coefficient. Edward Arnold (1990)
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© 2004 Springer-Verlag Berlin Heidelberg
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Laha, A. (2004). An Empirical Study on the Robustness of SOM in Preserving Topology with Respect to Link Density. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_21
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DOI: https://doi.org/10.1007/978-3-540-30499-9_21
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