in the two dimensional output space. The unsupervised process leads to the self organization of modeling with no previous knowledge of what is being modeled and therefore it does not model a predetermined environment. Taking the above into account feature selection was performed by analyzing the contributions of different sensor based features towards tool wear classification. It was found that...

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...

Monitoring of chemical processes is becoming increasingly difficult as a result of growing complexity and larger scale of operation. In this paper, Kohonen self-organizing map s (SOM) is used to monitor the operation of a lab-scale distillation column and to identify process states. SOM projects high -dimensional data to a lower two dimensional grid maps while preserving the metric relations of...

As digital music and sound collections increase in size there has been a lot of work in developing novel interfaces for browsing them. Many of these interfaces rely on automatic content analysis techniques to create representations that reflect similarities between the music pieces or sounds in the collection. Representations in 3D have the potential to convey more information but can be diffic...

A human spine is a complicated structure of bones, joints, ligaments and muscles which all undergo a process of change with age. This paper describes the use of artificial intelligence in visualization and better understanding of the progressive and degenerative changes in human lumbar spine. Visualizing this pattern of change will be helpful in finding the correlations among the spinal feature...

Self-organised maps (SOM) have been widely used for cluster analysis and visualisation purposes in exploratory data mining. In image retrieval applications, SOMs have been used to visualise high-dimensional feature space and build indexing structures. In this paper, we extend the use of SOMs for profiling and comparison of image collections, and present empirical results obtained in collection ...

The purpose of the study was to find out whether the conceptual connection of emotion and motion is holding in the domain of personality traits. In a quantitative study 40 Estonian terms of personality traits were investigated and a conclusion was driven that, indeed, the qualities of emotionality and motion are perceived as co-present characteristics. In further data analysis some visualized m...

This study explores the self-organizing neural network as a model of lexical and morphological acquisition. We examined issues of generalization, representation, and recovery in a multiple feature-map model. Our results indicate that self-organization and Hebbian learning are two important computational principles that can account for the psycholinguistic processes of semantic representation, m...

The reasons to use growing self-organizing networks are investigated. First an overview of several models of this kind is given are they are related to other approaches. Then two examples are presented to illustrate the speci c properties and advantages of incremental networks. In each case a non-incremental model is used for comparison purposes. The rst example is pattern classi cation and com...

Self-Organizing Feature map (SOFM) is a competitive neural network in which neurons are organized in an l-dimensional lattice (grid) representing the feature space. The principal goal of the SOFM is to transform an incoming pattern of arbitrary dimension into a oneor twodimensional discrete map, and to perform this transformation adaptively in a topologically ordered fashion. Usually, SOFM can ...