The feature map represented by the set of weight vectors of the basic SOM (Self-Organizing Map) provides a good approximation to the input space from which the sample vectors come. But the timedecreasing learning rate and neighborhood function of the basic SOM algorithm reduce its capability to adapt weights for a varied environment. In dealing with non-stationary input distributions and changi...

Self-organizing maps are artificial neural networks designed for unsupervised machine learning. They represent powerful data analysis tools applied in many different areas including areas such as biomedicine, bioinformatics, proteomics, and astrophysics. We maintain a data analysis package in R based on self-organizing maps. The package supports efficient, statistical measures that enable the u...

A Maximum-likelihood connectionist model for unsupervised learning over graphical domains

information from multidimensional primary signals, and to represent it as a location, say, in a two-dimensional network. Although this i s already a step towards generalization and symbolism, it must be admitted that the extraction of features from geometrically or physically relatable data elements i s still a very concrete task, in principle at least. Theoperation of the brain at the higher l...

We present a study of a novel variant of the Self-Organizing Map (SOM) called the Associative SelfOrganizing Map (A-SOM). The A-SOM is similar to the SOM and thus develops a representation of its input space, but in addition it also learns to associate its activity with the activity of one or several external SOMs. The A-SOM has relevance in e.g. the modelling of expectations in one modality du...

Self-Organizing map (SOM) is a widely used tool to find clustering and also to visualize high dimensional data. Several spherical SOMs have been proposed to create a more accurate representation of the data by removing the “border effect”. In this paper, we compare several spherical lattices for the purpose of implementation of a SOM. We then introduce a 2D rectangular grid data structure for r...

introduction:surgeosight is a dedicated intra-operative hand-held gamma camera designed and manufactured by our team to be used for lymphoscintigraphy. although conventional gamma cameras are widely used, they lack the capability of the sentinel lymph node (sln) imaging in the operation room. like conventional gamma cameras it is necessary to calibrate surgeosight for linearity distortion, ener...