Results 71 to 80 of about 19,078 (124)
The classification of the chain-link data by SOM (Spherical SOM, Torus-SOM, SOM_PAK)
Proceedings of the Fuzzy System Symposium, 2011 Tokutaka, Heizo +3 more
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Lean som fedtsugning eller styrketræning:Reflektioner som Lean som forbedringssystem [PDF]
, 2013 openaire
Hvidhed som vanearbejde - eller som mutationsprocess
Tidskrift för genusvetenskap, 2010 openaire +1 more source
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International Journal of Intelligent Systems Technologies and Applications, 2007
We propose a method to use the classification capabilities of self organising neural networks to extract symbolic information from raw data. The Multi-SOM (M-SOM) approach is a variant of Self Organising Maps (SOM). Multi-SOMS consist of a set of partner SOMs, trained simultaneously and in concurrence to each other, to adapt to different classes.
Nils Goerke +2 more
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We propose a method to use the classification capabilities of self organising neural networks to extract symbolic information from raw data. The Multi-SOM (M-SOM) approach is a variant of Self Organising Maps (SOM). Multi-SOMS consist of a set of partner SOMs, trained simultaneously and in concurrence to each other, to adapt to different classes.
Nils Goerke +2 more
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Neural Networks, 2006
Since the discovery of the SOM's by T. Kohonen, many results that provide a better description of their behaviour have been found. Most of them are very convincing, but from a mathematical point of view, only a few are actually proved. In this paper, we make a review of some results that are still to be proved and give some framework to formulate ...
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Since the discovery of the SOM's by T. Kohonen, many results that provide a better description of their behaviour have been found. Most of them are very convincing, but from a mathematical point of view, only a few are actually proved. In this paper, we make a review of some results that are still to be proved and give some framework to formulate ...
openaire +4 more sources
Neurocomputing, 1998
Many applications of self-organizing maps (SOM) require high computing performance in order to be efficient. Because of the regular and modular structure of SOMs, a custom hardware realization is obvious. Based on the idea of a massively parallel system, several chips have been designed, manufactured and tested by the authors.
Rüping, Stefan +2 more
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Many applications of self-organizing maps (SOM) require high computing performance in order to be efficient. Because of the regular and modular structure of SOMs, a custom hardware realization is obvious. Based on the idea of a massively parallel system, several chips have been designed, manufactured and tested by the authors.
Rüping, Stefan +2 more
openaire +3 more sources
1997
I introduce the T-SOM, an unsupervised neural network model based on well-known Kohonen Self-Organizing Maps. This model adds to SOM-properties the next new characteristics : a multiresolution knowledge representation, a low complexity algorithm and a simplified learning parameters tuning.
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I introduce the T-SOM, an unsupervised neural network model based on well-known Kohonen Self-Organizing Maps. This model adds to SOM-properties the next new characteristics : a multiresolution knowledge representation, a low complexity algorithm and a simplified learning parameters tuning.
openaire +2 more sources