The self-organizing map is one of the most prominent unsupervised learning architectures used to visualize the similarities of high-dimensional input structures. What remains by no means straightforward , is an explicit representation of cluster boundaries in the nal two-dimensional map display. The detection of these boundaries rather requires some amount of insight into the inherent structure...

To solve the mapping problem for the mobile robots in the unknown environment, a dynamic growing self-organizing map with growing-threshold tuning automatically algorithm (DGSOMGT) based on Self-organizing Map is proposed. It introduces a value of spread factor to describe the changing process of the growing threshold dynamically. The method realizes the network structure growing by training th...

Analysis of process data makes it possible to obtain useful information of processes or phenomena that are analytically difficult to deal with. To demonstrate the possibilities of this kind of approach, an analysis of the faults that occurred in a continuous digester is presented. The process data are fed to an artificial neural network, the Self-Organizing Map (SOM), which is used to form visu...

Estimation of emotions is an essential aspect in developing intelligent systems intended for crowded environments. However, emotion estimation in crowds remains a challenging problem due to the complexity in which human emotions are manifested and the capability of a system to perceive them in such conditions. This paper proposes a hierarchical Bayesian model to learn in unsupervised manner the...

Generating sounds for music composition with the desired timbral characteristics has been a challenge ever since the dawn of electroacoustic music. Timbre is a remarkably complex phenomenon that has puzzled researchers for a long time. Actually, the nature of musical signals is not fully understood yet. In this paper, we present a sound synthesis technique that uses Kohonen’s one-dimensional se...

The self-organizing map (SOM) converts statistical relationships between highdimensional data into geometric relationships on a low-dimensional grid. It can thus be regarded as a projection and a similarity graph of the primary data. As it preserves the most important topological relationships of the data elements on the display, it may be thought of as producing some form of abstraction. These...

Identifying structures in large data sets raises a number of problems. On the one hand, many methods cannot be applied to larger data sets, while, on the other hand, the results are often hard to interpret. We address these problems by a novel three-stage approach. First, we compute a small representation of the input data using a self-organizing map. This reduces the amount of data and allows ...

The VideoSOM sytem is a tool for content-based video navigation based on a growing self-organizing map. Our interface allows the user to browse the video content using simultaneously several perspectives, temporal as well as content-based representations of the video. Combined with the interaction possibilities between them this allows for efficient searching of relevant information in video co...

This paper describes a data organization system and genuine content-addressable memory called the WEBSOM. It is a two-layer self-organizing map (SOM) architecture where documents become mapped as points on the upper map, in a geometric order that describes the similarity of their contents. By standard browsing tools one can select from the map subsets of documents that are most similar mutually...