Advances in Self-Organizing Maps and Learning Vector Quantization

Part I. Self-Organizing Map Learning, Visualization, and Quality Assessment

1. Theoretical and Applied Aspects of the Self-Organizing Maps
Marie Cottrell, Madalina Olteanu, Fabrice Rossi, Nathalie Villa-Vialaneix

2. Aggregating Self-Organizing Maps with Topology Preservation
Jérôme Mariette, Nathalie Villa-Vialaneix

3. ESOM Visualizations for Quality Assessment in Clustering
Alfred Ultsch, Martin Behnisch, Jörn Lötsch

4. SOM Quality Measures: An Efficient Statistical Approach
Lutz Hamel

5. SOM Training Optimization Using Triangle Inequality
Denny, William Gozali, Ruli Manurung

6. Sparse Online Self-Organizing Maps for Large Relational Data
Madalina Olteanu, Nathalie Villa-Vialaneix

Part II. Clustering and Time Series Analysis with Self-Organizing Maps and Neural Gas

7. A Neural Gas Based Approximate Spectral Clustering Ensemble
Yaser Moazzen, Kadim Taşdemir

8. Reliable Clustering Quality Estimation from Low to High Dimensional Data
Jean-Charles Lamirel

9. Segment Growing Neural Gas for Nonlinear Time Series Analysis
Jorge R. Vergara, Pablo A. Estévez, Álvaro Serrano

10. Modeling Diversity in Ensembles for Time-Series Prediction Based on Self-Organizing Maps
Rigoberto Fonseca-Delgado, Pilar Gómez-Gil

Part III. Applications in Control, Planning, and Dimensionality Reduction, and Hardware for Self-Organizing Maps

11. Modular Self-Organizing Control for Linear and Nonlinear Systems
Paulo Henrique Muniz Ferreira, Aluízio Fausto Ribeiro Araújo

12. On Self-Organizing Map and Rapidly-Exploring Random Graph in Multi-Goal Planning
Jan Faigl

13. Dimensionality Reduction Hybridizations with Multi-dimensional Scaling
Oliver Kramer

14. A Scalable Flexible SOM NoC-Based Hardware Architecture
Mehdi Abadi, Slavisa Jovanovic, Khaled Ben Khalifa, Serge Weber, Mohamed Hédi Bedoui

15. Local Models for Learning Inverse Kinematics of Redundant Robots: A Performance Comparison
Humberto I. Fontinele, Davyd B. Melo, Guilherme A. Barreto

Part IV. Self-Organizing Maps in Neuroscience and Medical Applications

16. Using SOMs to Gain Insight into Human Language Processing
Risto Miikkulainen

17. Prototype-Based Spatio-Temporal Probabilistic Modelling of fMRI Data
Nahed Alowadi, Yuan Shen, Peter Tiňo

18. LVQ and SVM Classification of FDG-PET Brain Data
Deborah Mudali, Michael Biehl, Klaus L. Leenders, Jos B. T. M. Roerdink

19. Mutual Connectivity Analysis (MCA) for Nonlinear Functional Connectivity Network Recovery in the Human Brain Using Convergent Cross-Mapping and Non-metric Clustering
Axel Wismüller, Anas Z. Abidin, Adora M. DSouza, Mahesh B. Nagarajan

20. SOM and LVQ Classification of Endovascular Surgeons Using Motion-Based Metrics
Benjamin D. Kramer, Dylan P. Losey, Marcia K. O’Malley

21. Visualization and Practical Use of Clinical Survey Medical Examination Results
Masaaki Ohkita, Heizo Tokutaka, Nobuhiko Kasezawa, Eikou Gonda

22. The Effect of SOM Size and Similarity Measure on Identification of Functional and Anatomical Regions in fMRI Data
Patrick O’Driscoll, Erzsébet Merényi, Christof Karmonik, Robert Grossman

Part V. Learning Vector Quantization Theories and Applications I

23. Big Data Era Challenges and Opportunities in Astronomy—How SOM/LVQ and Related Learning Methods Can Contribute?
Pablo A. Estévez

24. Self-Adjusting Reject Options in Prototype Based Classification
T. Villmann, M. Kaden, A. Bohnsack, J.-M. Villmann, T. Drogies, S. Saralajew, B. Hammer

25. Optimization of Statistical Evaluation Measures for Classification by Median Learning Vector Quantization
D. Nebel, T. Villmann

26. Complex Variants of GLVQ Based on Wirtinger’s Calculus
Matthias Gay, Marika Kaden, Michael Biehl, Alexander Lampe, Thomas Villmann

27. A Study on GMLVQ Convex and Non-convex Regularization
David Nova, Pablo A. Estévez

Part VI. Learning Vector Quantization Theories and Applications II

28. Functional Representation of Prototypes in LVQ and Relevance Learning
Friedrich Melchert, Udo Seiffert, Michael Biehl

29. Prototype-Based Classification for Image Analysis and Its Application to Crop Disease Diagnosis
Ernest Mwebaze, Michael Biehl

30. Low-Rank Kernel Space Representations in Prototype Learning
Kerstin Bunte, Marika Kaden, Frank-Michael Schleif

31. Dynamic Prototype Addition in Generalized Learning Vector Quantization
Jonathon Climer, Michael J. Mendenhall

Keywords: Engineering, Computational Intelligence, Artificial Intelligence (incl. Robotics)