An efficient self-organizing map (E-SOM) learning algorithm using group of neurons

References

• T. Kohonen, Self-Organizing Maps, 3rd edn. (Springer-Verlag, Berlin Heidelberg, New York, 1995).
   Google Scholar
• Shu-Ling Shieh and I-En Liao, A new approach for data clustering and visualization using self-organizing maps, Expert Syst. Appl. 39 (2012) 11924–11933.
   Google Scholar
• Y. Cheng, Clustering with Competing Self-Organizing Maps, in Proc. Int. Joint Conf. on Neural Networks (IJCNN), (Baltimore, Maryland, 1992), pp. 785–790.
   Google Scholar
• W. Wan and D. Fraser, M2dSOMAP: Clustering and Classification of Remotely Sensed Imagery by Combining Multiple Kohonen Self-Organizing Maps and Associative Memory, in Proc. of Int. Joint Conf. on Neural Networks (IJCNN), (Piscataway, NJ, 1993), pp. 2464–2467.
   Google Scholar
• J. Vesanto and E. Alhoniemi, Clustering of the Self-Organizing Map, IEEE T. Neural Networ. 11 (3) (2002) 586–600.
   Web of Science ®Google Scholar
• Lapidot, H. Guterman and A. Cohen, Unsupervised Speaker Recognition Based on Competition between Self-Organizing Maps, IEEE T. Neural Networ. 13(4) (2002) 877–887.
   PubMed Web of Science ®Google Scholar
• D. Desieno, Adding a conscience to competitive learning, in Proc. of Int. Conf. on Neural Networks (ICNN), (Piscataway, NJ, 1988), pp. 117–124.
   Google Scholar
• L. Xu, A. Krzyzak, and E. Oja, Rival penalized competitive learning for clustering analysis, RBF net, and curve detection, IEEE T. Neural Networ. 4(4) (1993) 636–649.
   PubMed Web of Science ®Google Scholar
• Y. M. Cheung, Rival penalization controlled competitive learning for data clustering with unknown cluster number, in Proc. 9th Int. Conf. Neural Inf. Process., (Singapore, 2002), pp. 467–471.
   Google Scholar
• Y. M. Cheung, On rival penalization controlled competitive learning for clustering with automatic cluster number selection, IEEE T. Knowl. Data En. 17(11) (2005) 1583–1588.
   Web of Science ®Google Scholar
• Guénaël Cabanes, Younès Bennani and Dominique Fresneau, Enriched topological learning for cluster detection and visualization, Neural Networks 32 (2012) 186–195.
   PubMed Web of Science ®Google Scholar
• N. J. Mount and D. Weaver, Self-Organizing Maps and Boundary Effects: Quantifying the Benefits of Torus Wrapping for Mapping SOM Trajectories, Pattern Anal. Appl. 14 (2) (2011) 139–148.
   Google Scholar
• Y. Cheung and L. Law, Rival Model Penalized Self Organizing Map, IEEE T. Neural Networ. 18 (1) (2007) 289–295.
   PubMed Web of Science ®Google Scholar
• Matsushita Haruna and Nishio Yoshifumi, Self-Organizing Map with False Neighbor Degree between Neurons for Effective Self-Organization, in Proc. 6th Int. Workshop on Self-Organizing Maps (WSOM), (Bielefeld, Germany, 2007), pp. 1–6.
   Google Scholar
• Matsushita, H. and Nishio, Y., Self-Organizing Map with Weighted Connections avoiding false-neighbor effects, in Proc. of IEEE International Symposium on Circuits and Systems(ISCAS), (New York, 2010), pp. 2554–2557.
   Google Scholar
• Riccardo Rizzo, A New Training Method for Large Self Organizing Maps, Neural Process. Lett. 37 (2013) 263–275.
   Web of Science ®Google Scholar
• Antonio Neme and Pedro Miramontes, Self-Organizing Map Formation with a Selectively Refractory Neighborhood, Neural Process. Lett. 39 (2013) 1–24.
   Web of Science ®Google Scholar
• Van Hulle M, Topology-preserving map formation achieved with a purely local unsupervised competitive learning rule, Neural Networks 10(3) (1997) 431–446.
   Web of Science ®Google Scholar
• Bamford SA and AF Murray, Synaptic rewiring for topographic map formation and receptive field development, Neural Networks 23 (2010) 517–527.
   PubMed Web of Science ®Google Scholar
• Maia JEB, Barreto GA and Coelho ALV,Visual object tracking by an evolutionary self-organizing neural network, J. Intell. Fuzzy Syst. 22 (2011) 69–81.
   Web of Science ®Google Scholar
• Iren Valovaa, George Georgievb, Natacha Gueorguievac and Jacob Olsona, Initialization Issues in Self-organizing Maps, Procedia Computer Science 20 (2013) 52–57.
   Google Scholar
• H. Hasegawa, Optimization of Group Behavior, Jpn. Ethological Soc. Newslett. 43 (2004) 22–23.
   Google Scholar
• Joseph P.Herbert and JingTaoYao, A Granular Computing Framework for Self-Organizing Maps, Neurocomputing 72 (13-15) (2009) 2865–2872.
   Web of Science ®Google Scholar
• T. Kohonen, Self-Organizing Maps, 3rd edn. (Springer-Verlag, NewYork, 2001).
   Google Scholar
• H. Yang and M. Palaniswami, on the issue of neighborhood in self-organizing maps, in Proc. of Symp. Appl. Computing (ACM/SIGAPP),(Kansas USA, 1992), pp. 412–416.
   Google Scholar
• K. Kiviluoto, Topology preservation in self-organizing map, in Proc. of Int. Conf. on Neural Networks (ICNN), (Washington, USA, 1996), pp. 294–299.
   Google Scholar
• Bache, K. & Lichman, M., UCI Machine Learning Repository [ http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science (2013).
   Google Scholar