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Tau Aggregate Imaging and Transcriptomics of Alzheimer's Disease Brain at Different Stages of Disease. [PDF]

open access: yesAdv Sci (Weinh)
English EA   +9 more
europepmc   +1 more source

SOM of SOMs

open access: yesNeural Networks, 2009
This paper proposes an extension of the self-organizing map (SOM), in which the mapping objects themselves are self-organizing maps. Thus a "SOM of SOMs" is presented, which we refer to as a SOM(2). A SOM(2) has a hierarchical structure consisting of a single parent SOM and a set of child SOMs. Each child SOM is trained to represent the distribution of
Tetsuo Furukawa
exaly   +3 more sources
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Multi-SOMs for classification

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
openaire   +2 more sources

SOM’s mathematics

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 ...
openaire   +4 more sources

SOM accelerator system

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
openaire   +3 more sources

The T-SOM (Tree-SOM)

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.
openaire   +2 more sources

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