Self-Organizing Neural Networks
Recent Advances and Applications
278 pages, parution le 01/09/2001
Résumé
This compilation contains new theoretical work as well as
up-to-date applications contributed by some of the world
leaders of current SOM research. It is a compact and vivid
collection of almost all aspects of current research on
Self-Organizing Maps, ranging from theoretical work,
several technical and non-technical applications, numerical
and implementation details on sequential and parallel
hardware to self-organisation with spiking neurons. An
overture, given by Teuvo Kohonen, builds a bridge from the
development of the fundamentals to the many extensions,
modifications and applications which have made this neural
network architecture so successful.
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.
L'auteur - Lakhmi C. Jain
University of South Australia, Adelaide, SA,
Australia.
Editor
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Springer |
| Auteur(s) | Udo Seiffert, Lakhmi C. Jain |
| Parution | 01/09/2001 |
| Nb. de pages | 278 |
| Format | 16 x 24 |
| Couverture | Relié |
| Poids | 533g |
| Intérieur | Noir et Blanc |
| EAN13 | 9783790814170 |
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