Kohonen Maps (eBook)

Samuel Kaski, E. Oja (Herausgeber)

eBook Download: PDF

1999 | 1. Auflage
400 Seiten
Elsevier Science (Verlag)
978-0-08-053529-6 (ISBN)

Infos

The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm.

The 30 chapters of this book cover the current status of SOM theory, such as connections of SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.

Inhalt

Front Cover 1
Kohonen Maps 4
Copyright Page 5
Preface: Kohonen Maps 6
Table of Contents 8
Chapter 1. Analyzing and representing multidimensional quantitative and qualitative data: Demographic study of the Rhône valley. The domestic consumption of the Canadian families 12
Chapter 2. Value maps: Finding value in markets that are expensive 26
Chapter 3. Data mining and knowledge discovery with emergent Self-Organizing Feature Maps for multivariate time series 44
Chapter 4. From aggregation operators to soft Learning Vector Quantization and clustering algorithms 58
Chapter 5. Active learning in Self-Organizing Maps 68
Chapter 6. Point prototype generation and classifier design 82
Chapter 7. Self-Organizing Maps on non-Euclidean spaces 108
Chapter 8. Self-Organising Maps for pattern recognition 122
Chapter 9. Tree structured Self-Organizing Maps 132
Chapter 10. Growing self-organizing networks — history, status quo, and perspectives 142
Chapter 11. Kohonen Self-Organizing Map with quantized weights 156
Chapter 12. On the optimization of Self-Organizing Maps by genetic algorithms 168
Chapter 13. Self organization of a massive text document collection 182
Chapter 14. Document classification with Self-Organizing Maps 194
Chapter 15. Navigation in databases using Self-Organising Maps 208
Chapter 16. A SOM-based sensing approach to robotic manipulation tasks 218
Chapter 17. SOM-TSP: An approach to optimize surface component mounting on a printed circuit board 230
Chapter 18. Self-Organising Maps in computer aided design of electronic circuits 242
Chapter 19. Modeling self-organization in the visual cortex 254
Chapter 20. A spatio-temporal memory based on SOMs with activity diffusion 264
Chapter 21. Advances in modeling cortical maps 278
Chapter 22. Topology preservation in Self-Organizing Maps 290
Chapter 23. Second-order learning in Self-Organizing Maps 304
Chapter 24. Energy functions for Self-Organizing Maps 314
Chapter 25. LVQ and single trial EEG classification 328
Chapter 26. Self-Organizing Map in categorization of voice qualities 340
Chapter 27. Chemometric analyses with Self Organising Feature Maps: A worked example of the analysis of cosmetics using Raman spectroscopy 346
Chapter 28. Self-Organizing Maps for content-based image database retrieval 360
Chapter 29. Indexing audio documents by using latent semantic analysis and SOM 374
Chapter 30. Self-Organizing Map in analysis of large-scale industrial systems 386
Keyword index 400

Produkt-Details

• Erscheint lt. Verlag: 2.7.1999
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Mathematik / Informatik ► Informatik ► Netzwerke
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• Themenwelt: Informatik ► Theorie / Studium ► Algorithmen
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung
• ISBN-10: 0-08-053529-1 / 0080535291
• ISBN-13: 978-0-08-053529-6 / 9780080535296