Kalman filter implementation of self-organizing feature maps
Neural Computation
Measures for the organization of self-organizing maps
Self-Organizing neural networks
Generative probability density model in the self-organizing map
Self-Organizing neural networks
Extensions and modifications of the Kohenen-SOM and applications in remote sensing image analysis
Self-Organizing neural networks
Journal of VLSI Signal Processing Systems
A Novel Measure for Quantifying the Topology Preservation of Self-Organizing Feature Maps
Neural Processing Letters
Learning Vector Quantization for Multimodal Data
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Data Mining and Knowledge Discovery in Medical Applications Using Self-Organizing Maps
ISMDA '00 Proceedings of the First International Symposium on Medical Data Analysis
Statistical tools to assess the reliability of self-organizing maps
Neural Networks - New developments in self-organizing maps
Self-organizing maps with recursive neighborhood adaptation
Neural Networks - New developments in self-organizing maps
A self-organising network that grows when required
Neural Networks - New developments in self-organizing maps
Generalized relevance learning vector quantization
Neural Networks - New developments in self-organizing maps
Image denoising using self-organizing map-based nonlinear independent component analysis
Neural Networks - New developments in self-organizing maps
Expanding self-organizing map for data visualization and cluster analysis
Information Sciences: an International Journal - Special issue: Soft computing data mining
Supervised Neural Gas with General Similarity Measure
Neural Processing Letters
Neural maps in remote sensing image analysis
Neural Networks - 2003 Special issue: Neural network analysis of complex scientific data: Astronomy and geosciences
Recursive self-organizing network models
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Understanding and reducing variability of SOM neighbourhood structure
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Online data visualization using the neural gas network
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
A Structural Adapting Self-organizing Maps Neural Network
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Reconstruction Algorithms with Images Inferred by Self-organizing Maps
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Similarity-Based Clustering
Hierarchical PCA Using Tree-SOM for the Identification of Bacteria
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Self-Organizing Maps versus Growing Neural Gas in a Robotic Application
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
Topology Preserving Visualization Methods for Growing Self-Organizing Maps
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
On the role of hierarchy for neural network interpretation
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Using self-organizing maps to visualize high-dimensional data
Computers & Geosciences
Quantifying the Path Preservation of SOM-Based Information Landscapes
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
A relaxation algorithm influenced by self-organizing maps
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Fuzzy labeled self-organizing map for classification of spectra
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Scale-independent quality criteria for dimensionality reduction
Pattern Recognition Letters
Local matrix adaptation in topographic neural maps
Neurocomputing
Topology preserving SOM with transductive confidence machine
DS'10 Proceedings of the 13th international conference on Discovery science
Computer Science - Research and Development
Self organizing maps as models of social processes: the case of electoral preferences
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Relevance learning in unsupervised vector quantization based on divergences
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Design of a structured 3D SOM as a music archive
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Growing neural gas for vision tasks with time restrictions
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Statistical properties of lattices affect topographic error in self-organizing maps
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Perspectives of self-adapted self-organizing clustering in organic computing
BioADIT'06 Proceedings of the Second international conference on Biologically Inspired Approaches to Advanced Information Technology
Investigation of topographical stability of the concave and convex self-organizing map variant
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Cluster analysis of cortical pyramidal neurons using SOM
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
Detecting topology preserving feature subset with SOM
CIT'04 Proceedings of the 7th international conference on Intelligent Information Technology
Fuzzy labeled self-organizing map with label-adjusted prototypes
ANNPR'06 Proceedings of the Second international conference on Artificial Neural Networks in Pattern Recognition
Measuring GNG topology preservation in computer vision applications
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Fuzzy supervised self-organizing map for semi-supervised vector quantization
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Fuzzy neural gas for unsupervised vector quantization
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Expert Systems with Applications: An International Journal
Mimicking human neuronal pathways in silico: an emergent model on the effective connectivity
Journal of Computational Neuroscience
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The neighborhood preservation of self-organizing feature maps like the Kohonen map is an important property which is exploited in many applications. However, if a dimensional conflict arises this property is lost. Various qualitative and quantitative approaches are known for measuring the degree of topology preservation. They are based on using the locations of the synaptic weight vectors. These approaches, however, may fail in case of nonlinear data manifolds. To overcome this problem, in this paper we present an approach which uses what we call the induced receptive fields for determining the degree of topology preservation. We first introduce a precise definition of topology preservation and then propose a tool for measuring it, the topographic function. The topographic function vanishes if and only if the map is topology preserving. We demonstrate the power of this tool for various examples of data manifolds