The Self Organizing Maps (SOM) is regarded as an excellent computational tool that can be used in data mining and data exploration processes. The traditional SOM usually create a set of prototype vectors representing the data set and carries out a topology preserving projection of the prototypes ...
1.6 Self-organizing maps (SOMs): An unsupervised technique for seismic facies identification As mentioned previously, SOM is an unsupervised (feed-backward) machine learning technique that was first introduced by Kohonen in 1982 and is frequently used in many areas such as in technology, marketing ...
teikei - A web application that maps out community-supported agriculture based on crowdsourced data. (Demo) AGPL-3.0 Nodejs Conference Management ^ back to top ^ Software for submission of abstracts and preparation/management of academic conferences. Conference Organizing Distribution (COD) - Create ...
Several computational models of acquired and , including , have been proposed recently. In this paper, we use the framework of self-organizing maps to study several aspects of , by modeling abnormalities in the process in biologically plausible manners. We then interpret the resulting feature maps...
Self-organizing maps were first proposed by Teuvo Kohonen (Kohonen, 1982) and hence this technique is also known as Kohonen networks; it is sometimes also referred to by a more specific name, self-organizing feature maps. SOM methodology is used to project data objects from data space, mostly...
International Journal of Computational Intelligence 4;2 2008 An Ant-based Clustering System for Knowledge Discovery in DNA Chip Analysis Data There are many clustering algorithms such as hierarchical clustering, self-organizing maps, K-means clustering and so on. In this paper, we propose a ... ...
The self-organizing map (SOM) algorithm for finite data is derived as an approximate maximum a posteriori estimation algorithm for a gaussian mixture model with a gaussian smoothing prior, which is equivalent to a generalized deformable model (GDM). For this model, objective criteria for selecting...
Comparison to other neuromorphic self-organizing networks Unsupervised self-organizing networks have been previously studied on different hardware substrates, such as Self-organizing Maps (SOM) on Field Programmable Gate Array (FPGA)39, and reservoir computing using nano-wire networks40,41. The FPGA su...
This book constitutes the refereed proceedings of the 7th International Workshop on Advances in Self-Organizing Maps, WSOM 2009, held in St. Augustine, Florida, in June 2009. The 41 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers deal with ...
There are many ANN models, but self-organizing maps (SOMs) are fundamentally different in terms of architecture and learning algorithms. SOMs, also known as Kohonen maps, are based on biological studies of the cerebral cortex and were introduced in 1982 by [2], [3]. This model is an ANN...