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Fast Self-Organizing Of N-Dimensional Topology Maps
1996
Zenodo
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Publication in the conference proceedings of EUSIPCO, Trieste, Italy, 1996 ...
Right before the interpolation steps the fast algorithm converges to a well organized map ( gure 5 to 7). ...
Summary This paper proposes a self-growing fast algorithm for training n A -dimensional self-organizing feature maps. ...
doi:10.5281/zenodo.36125
fatcat:ly62ychzvbforc4afvrtpdaxsq
Modeling large cortical networks with growing self-organizing maps
2002
Neurocomputing
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Self-organizing computational models with specific intracortical connections can explain many features of visual cortex. ...
The scaling equations GLISSOM uses also allow comparison of biological maps and parameters between individuals and species with different brain region sizes. ...
the continuous map and then resampling it. ...
doi:10.1016/s0925-2312(02)00358-2
fatcat:ksihna46wre73fmn675smthsvm
A Vector Field Approach to Lexical Semantics
[chapter]
2015
Lecture Notes in Computer Science
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The computability of a vector field for the indexing vocabulary of the Reuters-21578 test collection by an emergent self-organizing map suggests that energy minima as learnables in machine learning presuppose ...
The approach used the distributional hypothesis to statistically model word meaning. We do not address the modelling of sentence meaning here. ...
Acknowledgement The authors are grateful for the comments of three anonymous reviewers. ...
doi:10.1007/978-3-319-15931-7_7
fatcat:ifqo4n6ifna3nlt4wgnq3qwgza
The Hierarchical Isometric Self-Organizing Map for Manifold Representation
2007
2007 IEEE Conference on Computer Vision and Pattern Recognition
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We present an algorithm, Hierarchical ISOmetric Self-Organizing Map (H-ISOSOM), for a concise, organized manifold representation of complex, non-linear, large scale, high-dimensional input data in a low ...
First, we modify the previous ISOSOM algorithm by a local linear interpolation (LLI) technique, which maps the data samples from low dimensional space back to high dimensional space and makes the complete ...
By integrating the self-organizing model with the geometric graph distance of Isomap, Guan [5] proposed an Isometric Self-Organizing Map (ISOSOM) method for concise, nonlinear manifold representation ...
doi:10.1109/cvpr.2007.383402
dblp:conf/cvpr/GuanT07
fatcat:4qzqwl6vercchmtlw24ipd5tra
Page 527 of Neural Computation Vol. 6, Issue 3
[page]
1994
Neural Computation
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The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
Along with muliilayered feedforward networks, Kohonen’s self-organizing mapping algorithm is one of the most popu- lar in robotics applications (see Brause 1990; Ritter et al. 1991). ...
Zs) (3.5)
Let us note, that the linear approximation 3.5 of the mapping 2.3 is continuous only piecewise. ...
Fast Interpolation Using Kohonen Self-Organizing Neural Networks
[chapter]
2000
Lecture Notes in Computer Science
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This paper proposes a new interpolation method based on Kohonen self-organizing networks. ...
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. ...
The authors wish to thank Didier Jourdan (CMO) for helpful comments and for making available a part of the MEDATLAS data set. ...
doi:10.1007/3-540-44929-9_11
fatcat:5bmdf5xcdzcx3pyhtpofv7j2ky
Nonlinear Independent Component Analysis by self-organizing maps
[chapter]
1996
Lecture Notes in Computer Science
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We show that such a mapping can be approximately realized using self-organizing maps with rectangular map topology. ...
More generally we can consider nonlinear mappings that make the components of the output vectors independent. ...
Self-Organizing Maps A self-organizing map (SOM) 12] performs a mapping from input space to an array of nodes in the output space. ...
doi:10.1007/3-540-61510-5_137
fatcat:xwex7tsbf5akjnnrb6oz5oagoe
System Identification Using Delaunay Tessellation of Self-Organizing Maps
[chapter]
2003
Neural Networks and Soft Computing
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The Self-Organizing Map (SOM) is a vector quantization method which places prototype vectors on a regular low-dimensional grid in an ordered fashion. ...
The operating regimes of the local linear models are obtained by the Delaunay tessellation of the codebook of the SOM. ...
Janos Abonyi is grateful for the financial support of the Janos Bolyai Research Fellowship of the Hungarian Academy of Science. ...
doi:10.1007/978-3-7908-1902-1_105
fatcat:e7rg654a3zewnie7jeslcxhi74
Scaling Laws for Mode Lockings in Circle Maps
1985
Physica Scripta
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The self-similar structure of mode lockings for circle maps is studied by means of the associated Farey trees. ...
We investigate numerically several classes of scaling relations implicit in the Farey organization of mode lockings and discuss the extent to which they lead to universal scaling laws. ...
The bulk of the work was done at Nordita. P.C. acknowledges support from DOE contract no. DE-ACO2-,. ' ' / ." ...
doi:10.1088/0031-8949/32/4/003
fatcat:b2s6ry4skbgxrd5nwx6tclcwia
A self-organizing Lagrangian particle method for adaptive-resolution advection–diffusion simulations
2012
Journal of Computational Physics
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We present a novel adaptive-resolution particle method for continuous parabolic problems. In this method, particles self-organize in order to adapt to local resolution requirements. ...
The method does not rely on any global transforms or mapping functions. ...
Sylvain Reboux was financed by a grant from the Swiss SystemsX.ch initiative (to Ivo F. Sbalzarini), Grant LipidX-2008/011, evaluated by the Swiss National Science Foundation. ...
doi:10.1016/j.jcp.2012.01.026
fatcat:mo3otmc73bhdzfuozecuz7ua7a
Spatiotemporal Types of HFMD and Climate
2011
Procedia - Social and Behavioral Sciences
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Using a self-organizing map (SOM) algorithm the dataset dimensionality was effectively reduced into 2 dimensions, while the spatiotemporal attribute structure was maintained. ...
Suspected climate attributes to HFMD were recorded monthly at 674 stations throughout the country and subsequently interpolated within 1456 11 cells across space-time (same as the number of HFMD cases) ...
Using a self-organizing map (SOM) algorithm the dataset dimensionality was effectively reduced into 2 dimensions, while the spatiotemporal attribute structure was maintained. ...
doi:10.1016/j.sbspro.2011.07.017
fatcat:agzgexqi6febndwvh6xzmqny3u
Geovisualization for Association Rule Mining in Oil and Gas Well Data
2017
ISPRS International Journal of Geo-Information
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The point-based method represents association rules based on well locations, and the surface-based method represents potentially applicable areas through spatial interpolation and visualization. ...
well locations and subsequent predictions based on the applicable areas of the rules are important. ...
Conflicts of Interest: The authors have no conflicts of interest to declare. ...
doi:10.3390/ijgi6020048
fatcat:kpjj5xtoqfhyvnuupnpiui5htq
Data interpolation using Kohonen networks
2000
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium
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The authors wish to thank Didier Jourdan (CMO) for helpful comments and for making available the Med data set. ...
Acknowledgment: This work was funded by the Service Hydrographique et Océanographique de la Marine (SHOM) under contract 98.87.054. ...
The paper is organized as follows. Section 2 recalls the backgrounds of kriging techniques. Section 3 describes the adaptation of self-organizing maps to the spatial interpolation problem. ...
doi:10.1109/ijcnn.2000.859396
dblp:conf/ijcnn/SarzeaudS00
fatcat:4eloea2qzzhm7jky5qu4lv55mu
Fast Binocular Depth Inference via Bidirectional Motion Based Interpolation
2014
Proceedings of International Conference on Internet Multimedia Computing and Service - ICIMCS '14
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Firstly, comparable accurate depth maps are generated for self-adaptive selected frames via stereo matching. ...
Then rough depth sequences inbetween are calculated using bidirectional motion-based interpolation. ...
To save computational time and keep the depth maps temporal continuous, we utilize a motion-based linear interpolation, which is defined as: D K (x + αu, y + αv) = αDm(x, y) + (1 − α)Dn(x + u, y + v) ( ...
doi:10.1145/2632856.2632872
dblp:conf/icimcs/GengYJRW14
fatcat:xbssti6hwrc6tn62r5cvulf4hq
Effect of SRTM resolution on morphometric feature identification using neural network—self organizing map
2009
Geoinformatica
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Self Organizing Map (SOM) is used for the classification of morphometric parameters into ten exclusive and exhaustive classes. ...
In this study, we present a semi-automatic procedure using Neural Networks-Self Organizing Map-and Shuttle Radar Topography Mission DEMs to characterize morphometric features of the landscape in the Man ...
Acknowledgement We are grateful to the Swedish Institute for funding all travel expenses in the framework of the Visby program. ...
doi:10.1007/s10707-009-0085-4
fatcat:r3qjyix575d2talojv62tpxkxu
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