We invite contributions related to the theoretical and methodological aspects of Self-Organizing Maps, Learning Vector Quantization and closely related topics including:

• Data analysis and visualization
• Various mathematical approaches including information theory and mathematical statistics
• Software and hardware implementations
• Architectural solutions including hierarchical and growing networks, ensemble models and special metrics
• Neuro-cognitive studies that compare modeling and empirical results at different levels
• Models, experimental investigations and applications of autonomous mental development.

We also call for scientific and practice-oriented papers that demonstrate the use of SOM, LVQ and their variants in different application areas including but not limited to:

• Data mining
• Pattern recognition
• Signal processing
• Knowledge management
• Time series processing
• Modeling dynamic phenomena
• Industrial applications
• Bioinformatics
• Biomedical applications
• Telecommunications
• Financial analysis
• Cognitive modeling
• Language modeling
• Robotics and intelligent systems
• Image processing and vision
• Speech processing
• Text and document analysis

Publication

All accepted papers will be published by Springer in their Advances in Intelligent Systems and Computing book series and at http://www.springer.com/.