The Self-Organising Map (SOM), with its related techniques, is one of the most popular and powerful concepts for unsupervised pattern recognition and data visualisation. Over 3,000 applications have been reported in the open literature, and many commercial projects employ the SOM as the tool for tackling real-world problems. This volume is a complete record of the Third Workshop on Self-Organising Maps, which brought together the leading international researchers and users for an intensive three-day meeting in Lincoln, UK, and so represents the very latest developments in both theory and application of SOMs and associated approaches. Topics covered include: - Pattern recognition and data clustering; - Unsupervised learning using SOMs and other techniques; - Data visualisation; - Commercial and financial applications; - Multi-dimensional signal processing; - Component and system design and condition monitoring.
