Self-organizing neural networks

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The Self-Organizing Map (SOM) is a widely utilized architecture for unsupervised artificial neural networks, introduced by Teuvo Kohonen in the 1980s. It has become a powerful method for visualization and unsupervised classification, thanks to a vibrant community of international researchers who have developed numerous extensions and modifications over the past two decades. The original algorithm's strength lies in its universal applicability and ease of use, requiring only a few parameters, making it accessible even for beginners while still delivering reliable results. This book showcases the latest theoretical advancements and presents a variety of challenging real-world applications, demonstrating the ongoing potential for improvements and innovative developments in the field. The extensive range of published applications utilizing SOMs is remarkable. Our objective is to provide a contemporary overview of self-organizing neural networks, making it accessible to researchers, practitioners, and graduate students across various academic and industrial disciplines. We extend our gratitude to Professor Teuvo Kohonen, the pioneer of SOMs, for his support and for contributing the first chapter of this book.