Self-Organizing Neural Networks Recent Advances and Applications /

The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s, SOMs have been developed as a very powerful method for visualization and unsupervised classification tasks by an active and innovative...

Full description

Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Seiffert, Udo (Editor, http://id.loc.gov/vocabulary/relators/edt)
Format: Electronic eBook
Language:English
Published: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2002.
Edition:1st ed. 2002.
Series:Studies in Fuzziness and Soft Computing, 78
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • Overture
  • Measures for the Organization of Self-Organizing Maps
  • Unsupervised Learning and Self-Organization in Networks of Spiking Neurons
  • Generative Probability Density Model in the Self-Organizing Map
  • Growing Multi-Dimensional Self-Organizing Maps for Motion Detection
  • Extensions and Modifications of the Kohonen-SOM and Applications in Remote Sensing Image Analysis
  • Modeling Speech Processing and Recognition in the Auditory System Using the Multilevel Hypermap Architecture
  • Algorithms for the Visualization of Large and Multivariate Data Sets
  • Self-Organizing Maps and Financial Forecasting: an Application
  • Unsupervised and Supervised Learning in Radial-Basis-Function Networks
  • Parallel Implementations of Self-Organizing Maps.