We propose a new self-organizing neural model that performs principal components analysis. It is also related to the adaptive subspace self-organizing map (ASSOM) network, but its training equations are simpler. Experimental results are reported, which show that the new model has better performance than the ASSOM network.

Self-organization has been investigated for long in a very broad range of areas. However, only till recently has self-managing and self-organizing computing received intensive attention. The purpose of this paper is to discuss some of important basic problems of selfmanaging and self-organizing computing, including the essence of self-managing computing, generic architecture of computing, real ...

This work is focused on the design and evaluation of a suboptimal classifier for dysarthria assessment. The classification relied on self organizing maps to discriminate 8 types of dysarthria and a normal group. The classification technique provided an excellent accuracy for assessment and enabled clinicians with a powerful relevance analysis of the input features. This technique also allows a ...

We present an approach based on self organizing maps to segment renal arteries from 2D PC Cine MR images to measure blood velocity and flow. Such information are important in grading renal artery stenosis and support the decision on surgical interventions like percutan transluminal angioplasty. Results show that the renal arteries could be extracted automatically. The corresponding velocity pro...

In this article, we introduce the concept of pathways of wellbeing and examine how such paths can be discovered from large data sets using the self-organizing map. Data sets used in the illustrative experiments include measurements of physical fitness and subjective assessments related to diagnosing work stress.

This paper discusses the application of a GH-SOM architecture to the problem of Handwritten Digit Recognition. The results proved to be better than the ones obtained from standard SOM networks.

The Seismic Research Centre, University of the West Indies operates a seismic network that performs suboptimally in detecting, locating, and correctly determining the magnitude of earthquakes due to a diverse constituion of seismometers and the utilization of a site selection process that approximates an educated guess. My work seeks to apply Self-Organizing Maps (SOM) to arrive at the optimal ...