Neural Networks
Self-Organizing Maps
Neural and Adaptive Systems: Fundamentals through Simulations with CD-ROM
Neural and Adaptive Systems: Fundamentals through Simulations with CD-ROM
Recursive self-organizing maps
Neural Networks - New developments in self-organizing maps
Recursive self-organizing network models
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Dynamics and Topographic Organization of Recursive Self-Organizing Maps
Neural Computation
Incremental Unsupervised Time Series Analysis Using Merge Growing Neural Gas
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Gamma SOM for Temporal Sequence Processing
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Neurocomputing
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In this paper, we introduce the Gamma Growing Neural Gas (?-GNG) model for temporal sequence processing. The standard GNG is merged with a context descriptor based on a short term memory structure called Gamma memory. When using a single stage of the Gamma filter, the Merge GNG model is recovered. The γ-GNG model is compared to γ-Neural Gas, γ-SOM, and Merge Neural Gas, using the temporal quantization error as a performance measure. Simulation results on two data sets are presented: Mackey-Glass time series, and Bicup 2006 challenge time series.