Advances in Self-Organizing Maps

Self-organizing maps (SOMs) were developed by Teuvo Kohonen in the early eighties. Since then more than 10,000 works have been based on SOMs. SOMs are unsupervised neural networks useful for clustering and visualization purposes. Many SOM applications have been developed in engineering and science, and other fields.

This book contains refereed papers presented at the 9^th Workshop on Self-Organizing Maps (WSOM 2012) held at the Universidad de Chile, Santiago, Chile, on December 12-14, 2012. The workshop brought together researchers and practitioners in the field of self-organizing systems. Among the book chapters there are excellent examples of the use of SOMs in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis, and time series analysis. Other chapters present the latest theoretical work on SOMs as well as Learning Vector Quantization (LVQ) methods.

• Complexity
• Data Mining
• Intelligent Systems
• Self-Organizing Maps

• , Department of Electrical Engineering, University of Chile, Santiago, Chile

  Pablo A. Estévez

• , Computational NeuroEngineering Lab., University of Florida, Gainesville, USA

  José C. Príncipe

• , Facultad de Ingeniería y, Universidad de los Andes, Santiago, Chile

  Pablo Zegers

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