Important and relevant information is expected to be encoded in local structural elements of proteins. An unsupervised learning algorithm (Kohonen algorithm) was applied to the representation and unbiased classification of local backbone structures contained in a set of proteins. Training yielded a two-dimensional Kohonen feature map with 100 different structural motifs including certain helica...

The availability of linguistic corpora in electronic form has made it possible to make various kinds of computer-based analyses on them. The use of Self-Organizing Map (SOM) in the analysis and visualization of various aspects of textual material is outlined. The basic approach for creating maps of lexical items, documents, or set of languages or dialects is described with reference to original...

A performance comparison of two self-organizing networks, the Kohonen Feature Map and the recently proposed Growing Cell Structures is made. For this purpose several performance criteria for self-organizing networks are proposed and motivated. The models are tested with three example problems of increasing difficulty. The Kohonen Feature Map demonstrates slightly superior results only for the s...

This paper presents an action selection framework based on an assemblage of self-organizing neural networks called Cooperative Extended Kohonen Maps. This framework encapsulates two features that significantly enhance a robot’s action selection capability: self-organization in the continuous state and action spaces to provide smooth, efficient and fine motion control; action selection via the c...

The measurement of living standards is widely recognized to be a multivariate challenge. In this paper, problems with the use of typical univariate indicators are outlined, and a novel approach is suggested which relies on Kohonen maps. The stability and accuracy of the map are evaluated via a bootstrap methodology. This paper presents an application of the technique of Kohonen maps in the cont...

Künstliche Neuronale Netze (KNN), insbesondere Kohonen-Netze, sind zur Klassifizierung von Daten geeignet, da sie die topologischen Eigenschaften von Eingabedaten hoher Dimensionalität auf einen niedrigdimensionalen Raum (Ebene) abbilden können. Die Implementierung der Kohonen-Netze wird auf Transputern realisiert, da hier die inhärente Parallelität der Neuronen auf eine parallele Verarbeitung ...

Physical data interpolation is a common issue in Geosciences. For many variable of interest, the measurements are often sparse and irregularly distributed in time and space. Analyzing the data usually requires a numerical model, which samples the data on a regular grid. Mapping irregular measurements on a regular grid is done by interpolation, which aims to generalize, but not to create, inform...

The Fuzzy Kohonen Clustering Network combines the idea of fuzzy membership values for learning rates. It is a kind of self-organizing fuzzy neural network that can show great superiority in processing the ambiguity and the uncertainty of data sets or images. Symbolic data analysis provides suitable tools for managing aggregated data described by intervals. This paper introduces Fuzzy Kohonen Cl...