Advances in Self-Organizing Maps and Learning Vector Quantization

Chapter 1 Theoretical and Applied Aspects of the Self-Organizing Maps

Chapter 2 Aggregating Self-Organizing Maps with Topology Preservation

Chapter 3 ESOM Visualizations for Quality Assessment in Clustering

Chapter 4 SOM Quality Measures: An Efficient Statistical Approach

Chapter 5 SOM Training Optimization Using Triangle Inequality

Chapter 6 Sparse Online Self-Organizing Maps for Large Relational Data

Chapter 7 A Neural Gas Based Approximate Spectral Clustering Ensemble

Chapter 8 Reliable Clustering Quality Estimation from Low to High Dimensional Data

Chapter 9 Segment Growing Neural Gas for Nonlinear Time Series Analysis

Chapter 10 Modeling Diversity in Ensembles for Time-Series Prediction Based on Self-Organizing Maps

Chapter 11 Modular Self-Organizing Control for Linear and Nonlinear Systems

Chapter 12 On Self-Organizing Map and Rapidly-Exploring Random Graph in Multi-Goal Planning

Chapter 13 Dimensionality Reduction Hybridizations with Multi-dimensional Scaling

Chapter 14 A Scalable Flexible SOM NoC-Based Hardware Architecture

Chapter 15 Local Models for Learning Inverse Kinematics of Redundant Robots: A Performance Comparison

Chapter 16 Using SOMs to Gain Insight into Human Language Processing

Chapter 17 Prototype-Based Spatio-Temporal Probabilistic Modelling of fMRI Data

Chapter 18 LVQ and SVM Classification of FDG-PET Brain Data

Chapter 19 Mutual Connectivity Analysis (MCA) for Nonlinear Functional Connectivity Network Recovery in the Human Brain Using Convergent Cross-Mapping and Non-metric Clustering

Chapter 20 SOM and LVQ Classification of Endovascular Surgeons Using Motion-Based Metrics

Chapter 21 Visualization and Practical Use of Clinical Survey Medical Examination Results

Chapter 22 Advances in Self-Organizing Maps and Learning Vector Quantization

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

Chapter 24 Self-Adjusting Reject Options in Prototype Based Classification

Chapter 25 Optimization of Statistical Evaluation Measures for Classification by Median Learning Vector Quantization

Chapter 26 Complex Variants of GLVQ Based on Wirtinger’s Calculus

Chapter 27 A Study on GMLVQ Convex and Non-convex Regularization

Chapter 28 Functional Representation of Prototypes in LVQ and Relevance Learning

Chapter 29 Prototype-Based Classification for Image Analysis and Its Application to Crop Disease Diagnosis

Chapter 30 Low-Rank Kernel Space Representations in Prototype Learning

Chapter 31 Dynamic Prototype Addition in Generalized Learning Vector Quantization