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Randomized Self-Organizing Map

Nicolas P. Rougier, Georgios Is. Detorakis
2021 Neural Computation  
We also demonstrate the ability of the randomized self-organizing map to gracefully reorganize itself in case of neural lesion and/or neurogenesis.  ...  We propose a variation of the self-organizing map algorithm by considering the random placement of neurons on a two-dimensional manifold, following a blue noise distribution from which various topologies  ...  A constant issue with self-organizing maps is how to measure the quality of a map.  ... 
doi:10.1162/neco_a_01406 pmid:34310672 fatcat:eqr7j5v7ebf3bncewl5bzg6wme

Mapping the Gnutella network

R. Matei, A. Iamnitchi, P. Foster
2002 IEEE Internet Computing  
We captured the network's topology, generated traffic, and dynamic behavior to determine its connectivity structure and how well (if at all) Gnutella's overlay network topology maps to the physical Internet  ...  the decentralized nature of pure P2P systems means that these are emergent properties, determined by local decisions made by individual resources based only on local infor-mation: We are dealing with a self-organized  ...  This research was supported in part by the U.S. National Science Foundation under contract ITR-0086044.  ... 
doi:10.1109/4236.978369 fatcat:qtexbzftq5atvgdvdckg5c6x2y

Automated Mapping of Hydrographic Systems from Satellite Imagery Using Self-Organizing Maps and Principal Curves [chapter]

Marek B.
2011 Self Organizing Maps - Applications and Novel Algorithm Design  
Topology of a three-feature self-organizing map In this application, the definition of the input vector consists in finding a discriminative set of spectral bands from Table 1 .  ...  The mapping from the space of spectral features to the space of terrain classes is performed by a self-organizing feature map (SOM) architecture.  ... 
doi:10.5772/13927 fatcat:epmgvixwrndurcjorx2jx5jxgm

Dynamic Cell Structure Learns Perfectly Topology Preserving Map

Jörg Bruske, Gerald Sommer
1995 Neural Computation  
utilize perfectly topology preserving feature maps for adaptation and in- terpolation.  ...  DCS Learns Topology Preserving Map 865 Villmann, T., Der, R., and Martinetz, T. 1994. A novel approach to measure the topology preservation of feature maps. Proc. ICANN 94 298-301.  ... 
doi:10.1162/neco.1995.7.4.845 fatcat:p7btrtedknfaflzd5rweoceqoy

Nonlinear Mapping Networks

Dimitris K. Agrafiotis, Victor S. Lobanov
2000 Journal of chemical information and computer sciences  
to reproduce the topology and structure of the data space in a faithful and unbiased manner.  ...  Among the many dimensionality reduction techniques that have appeared in the statistical literature, multidimensional scaling and nonlinear mapping are unique for their conceptual simplicity and ability  ...  ., for his insightful comments and support of this work.  ... 
doi:10.1021/ci000033y pmid:11128094 fatcat:to5f2wajtjfcrmkeniyqdkje2i

Learning Nonlinear Principal Manifolds by Self-Organising Maps [chapter]

Hujun Yin
2008 Lecture Notes in Computational Science and Engineering  
This chapter provides an overview on the self-organised map (SOM) in the context of manifold mapping. It first reviews the background of the SOM and issues on its cost function and topology measures.  ...  Then its variant, the visualisation induced SOM (ViSOM) proposed for preserving local metric on the map, is introduced and reviewed for data visualisation.  ...  Thus the C measure is also the objective function of the mapping, an important property different from other topology preservation measures and definitions.  ... 
doi:10.1007/978-3-540-73750-6_3 fatcat:47bnyroyebc7tmhb24vwxdqwnu

Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes [chapter]

Thomas Villmann, Udo Seiffert, Frank-Michael Schleif, Cornelia Brüß, Tina Geweniger, Barbara Hammer
2006 Lecture Notes in Computer Science  
We extend the self-organizing map (SOM) in the form as proposed by Heskes to a supervised fuzzy classification method.  ...  On the other hand, the integration of labeling into the location of prototypes in a SOM leads to a visualization of those parts of the data relevant for the classification.  ...  This work was supported by a grant of the German Federal Ministry of Education and Research (No. 0312706A).  ... 
doi:10.1007/11829898_5 fatcat:6hdjxhxqlndd5kgnebllfzq4gm

The Self-Organizing Maps: Background, Theories, Extensions and Applications [chapter]

Hujun Yin
2008 Studies in Computational Intelligence  
Background Kohonen's self-organizing map (SOM) is an abstract mathematical model of topographic mapping from the (visual) sensors to the cerebral cortex.  ...  This Section looks into the relevant biological models, from two fundamental phenomena involved -lateral inhibition and Hebbian learning -to Willshaw and von der Malsburg's self-organization retinotopic  ...  Thus the C measure is also the objective function of the mapping, an important property different from other topology preservation measures and definitions.  ... 
doi:10.1007/978-3-540-78293-3_17 fatcat:5fxzbyyoofd2ppfrnncyqfji6m

Topographic Mapping of Dissimilarity Data [chapter]

Barbara Hammer, Andrej Gisbrecht, Alexander Hasenfuss, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu
2011 Lecture Notes in Computer Science  
Often, electronic data are inherently non-Euclidean and modern data formats are connected to dedicated non-Euclidean dissimilarity measures for which classical topographic mapping cannot be used.  ...  Topographic mapping offers a very flexible tool to inspect large quantities of high-dimensional data in an intuitive way.  ...  Further, financial support from the Cluster of Excellence 277 Cognitive Interaction Technology funded in the framework of the German Excellence Initiative is gratefully acknowledged.  ... 
doi:10.1007/978-3-642-21566-7_1 fatcat:rrb7l3ehone3zic6xhpclwpl6a

A multilayer self-organizing feature map for range image segmentation

Jean Koh, Minsoo Suk, Suchendra M. Bhandarkar
1995 Neural Networks  
The multilayer self-organizing feature map (MLSOFM), which is an extension of the traditional (singlelayer ) self-organizing feature map ( SOFM) is seen to alleviate the shortcomings of the latter in the  ...  This paper proposes and describes a hierarchical self-organizing neural network for range image segmentation.  ...  The multilayer self-organizing feature map (MLSOFM) that we have proposed (Suk & Koh, 1993) combines the ideas of self-organization and topographic mapping with those of multiscale image segmentation  ... 
doi:10.1016/0893-6080(94)00061-p fatcat:wiud6x3bgfgddmaab255yndwv4

Competitive learning for Self Organizing Maps used in classification of partial discharge

R. Jaramillo-Vacio, A. Ochoa-Zezzatti, A. Rios-Lira, J. Ponce
2012 CONIELECOMP 2012, 22nd International Conference on Electrical Communications and Computers  
maps, partial discharge, quality measurements, diagnosis.  ...  para mapas autoorganizados utilizados en clasificación de descargas parciales aprendizaje competitivo, mapas autoorganizados, descargas parciales, métricas de calidad, diagnóstico. competitive learning, self-organizing  ...  Resolution and topology preservation are generally used to measure SOM quality. There are many ways to measure it. The quantization error (qe) is calculated to measure the quality of the map.  ... 
doi:10.1109/conielecomp.2012.6189910 dblp:conf/conielecomp/Jaramillo-VacioORP12 fatcat:22rouzkdrveb5btzlsh2jb4nka

Music Mood Visualization Using Self-Organizing Maps

Magdalena Plewa, Bożena Kostek
2015 Archives of Acoustics  
The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps.  ...  A map is created in which music excerpts with similar mood are organized next to each other on the two-dimensional display.  ...  PBS1/B3/16/2012 entitled "Multimodal system supporting acoustic communication with computers" financed by the Polish National Centre for Research and Development.  ... 
doi:10.1515/aoa-2015-0051 fatcat:4emhot3rrnapzdwl6cbj7ecina

On Computing Mapping of 3D Objects

Xin Li, S. S. Iyengar
2014 ACM Computing Surveys  
Effective mapping benefits many scientific and engineering tasks that involve the modeling and processing of correlated geometric or image data.  ...  Different mapping algorithms are discussed and compared according to their formulations of objective functions, constraints, and optimization strategies.  ...  no self-deformations.  ... 
doi:10.1145/2668020 fatcat:rcwzp5d4azb7xkaquyfc3l3reu

Stronger Forms of Sensitivity for Measure-Preserving Maps and Semiflows on Probability Spaces

Risong Li, Yuming Shi
2014 Abstract and Applied Analysis  
It is shown that, on a metric probability space with a fully supported measure, if a measure-preserving map is weak mixing, then it is ergodically sensitive and multisensitive; and if it is strong mixing  ...  Similar results for measure-preserving semiflows are obtained, where it is required in a result about ergodic sensitivity that the space is compact in some sense and the semiflow is continuous.  ...  Acknowledgments The authors sincerely thank the referees for their careful reading and useful remarks, which helped us improve the paper.  ... 
doi:10.1155/2014/769523 fatcat:w5lhpbrrifa35hjcxwdemxj7tm

Mapping the Gnutella Network: Properties of Large-Scale Peer-to-Peer Systems and Implications for System Design [article]

Matei Ripeanu, Ian Foster, Adriana Iamnitchi
2002 arXiv   pre-print
The open architecture, achieved scale, and self-organizing structure of the Gnutella network make it an interesting P2P architecture to study.  ...  We have built a "crawler" to extract the topology of Gnutella's application level network. In this paper we analyze the topology graph and evaluate generated network traffic.  ...  This research was supported in part by the National Science Foundation under contract ITR-0086044.  ... 
arXiv:cs/0209028v1 fatcat:fa2bso4kjncepelpz2vx2saqcy
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