Titlebook: Advances in Self-Organizing Maps; 8th International Wo Jorma Laaksonen,Timo Honkela Conference proceedings 2011 Springer-Verlag GmbH Berlin

Mediocre

Growing Graph Network Based on an Online Gaussian Mixture Modelussian kernels and finding topologies between kernels using graph paths. The proposed method has the following advantages compared with conventional growing neural networks: no permanent increase in nodes (Gaussian kernels), robustness to noise, and increased speed of constructing networks. This pap

lavish

MIR

Coeval

ARBOR

Gamma-Filter Self-Organizing Neural Networks for Time Series Analysiscriptor 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 .-GNG model is compared to .-Neural Gas, .-SOM, and Merge Neural Gas, using the temporal quantization error as a performance measure. Simulation re

波動

backdrop

Carcinogen

A Discussion on Visual Interactive Data Exploration Using Self-Organizing Mapst users in data exploration tasks, a series of software tools emerged which integrate various visualizations. However, the focus of most research was the development of visualizations which improve the support in cluster identification. In order to provide real insight into the data set it is crucia

Simulate

堅(jiān)毅

Assessing the Efficiency of Health Care Providers: A SOM Perspective providers is completely new; (b) SOM graph mining shows, in turn, elements of innovations for the way the adjacency matrix is formed, with the connections among SOM winner nodes used as starting point to the process.