A Novel Measure for Quantifying the Topology Preservation of Self-Organizing Feature Maps
Neural Processing Letters
Piecewise Linear Projection Based on Self-Organizing Map
Neural Processing Letters
Adaptive double self-organizing maps for clustering gene expression profiles
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Expanding self-organizing map for data visualization and cluster analysis
Information Sciences: an International Journal - Special issue: Soft computing data mining
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Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Expert Systems with Applications: An International Journal
Case-Based Reasoning Adaptation for High Dimensional Solution Space
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
DS '08 Proceedings of the 11th International Conference on Discovery Science
Exploring Topology Preservation of SOMs with a Graph Based Visualization
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
A swarm-inspired projection algorithm
Pattern Recognition
Exploiting data topology in visualization and clustering of self-organizing maps
IEEE Transactions on Neural Networks
Community self-organizing map and its application to data extraction
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A new approach to clustering data with arbitrary shapes
Pattern Recognition
Clustering evaluation in feature space
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Graph based representations of density distribution and distances for self-organizing maps
IEEE Transactions on Neural Networks
Computer Science - Research and Development
Kernel PCA as a visualization tools for clusters identifications
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Fuzzy self-organizing map neural network using kernel PCA and the application
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Improvement of data visualization based on ISOMAP
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
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In this paper a new model of self-organizing neural networks is proposed. An algorithm called “double self-organizing feature map” (DSOM) algorithm is developed to train the novel model. By the DSOM algorithm the network will adaptively adjust its network structure during the learning phase so as to make neurons responding to similar stimulus have similar weight vectors and spatially move nearer to each other at the same time. The final network structure allows us to visualize high-dimensional data as a two dimensional scatter plot. The resulting representations allow a straightforward analysis of the inherent structure of clusters within the input data. One high-dimensional data set is used to test the effectiveness of the proposed neural networks