scholarly journals Clustering by Fuzzy Neural Gas and Evaluation of Fuzzy Clusters

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Tina Geweniger ◽  
Lydia Fischer ◽  
Marika Kaden ◽  
Mandy Lange ◽  
Thomas Villmann
Keyword(s):  
Simulated Annealing ◽  
Vector Quantization ◽  
Self Organizing Maps ◽  
Fuzzy C Means ◽  
Neural Gas ◽  
Fuzzy Neural ◽  
Evaluation Measure ◽  
Fuzzy Vector Quantization ◽  
Fuzzy Vector ◽  
Self Organizing

We consider some modifications of the neural gas algorithm. First, fuzzy assignments as known from fuzzy c-means and neighborhood cooperativeness as known from self-organizing maps and neural gas are combined to obtain a basic Fuzzy Neural Gas. Further, a kernel variant and a simulated annealing approach are derived. Finally, we introduce a fuzzy extension of the ConnIndex to obtain an evaluation measure for clusterings based on fuzzy vector quantization.

scholarly journals Magnification Control in Self-Organizing Maps and Neural Gas

2006 ◽  
Vol 18 (2) ◽  
pp. 446-469 ◽  
Author(s):  
Thomas Villmann ◽  
Jens Christian Claussen
Keyword(s):  
Vector Quantization ◽  
Dimensional Case ◽  
Control Mechanisms ◽  
General Description ◽  
Self Organizing Maps ◽  
One Dimensional ◽  
Neural Gas ◽  
The One ◽  
Localized Learning ◽  
Self Organizing

We consider different ways to control the magnification in self-organizing maps (SOM) and neural gas (NG). Starting from early approaches of magnification control in vector quantization, we then concentrate on different approaches for SOM and NG. We show that three structurally similar approaches can be applied to both algorithms that are localized learning, concave-convex learning, and winner-relaxing learning. Thereby, the approach of concave-convex learning in SOM is extended to a more general description, whereas the concave-convex learning for NG is new. In general, the control mechanisms generate only slightly different behavior comparing both neural algorithms. However, we emphasize that the NG results are valid for any data dimension, whereas in the SOM case, the results hold only for the one-dimensional case.

scholarly journals A Massively Parallel Algorithm for Fuzzy Vector Quantization

2009 ◽  
Vol 16A (6) ◽  
pp. 411-418 ◽  
Author(s):  
Luong Van Huynh ◽  
Cheol-Hong Kim ◽  
Jong-Myon Kim
Keyword(s):  
Parallel Algorithm ◽  
Vector Quantization ◽  
Massively Parallel ◽  
Fuzzy Vector Quantization ◽  
Fuzzy Vector

scholarly journals Self-organizing Maps versus Growing Neural Gas in Detecting Anomalies in Data Centres

2015 ◽  
Vol 23 (3) ◽  
pp. 495-505 ◽  
Author(s):  
M. Zapater ◽  
D. Fraga ◽  
P. Malagon ◽  
Z. Bankovic ◽  
J. M. Moya
Keyword(s):  
Self Organizing Maps ◽  
Growing Neural Gas ◽  
Neural Gas ◽  
Data Centres ◽  
Self Organizing
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