Neural networks primer, part IV
AI Expert
Generalized relevance learning vector quantization
Neural Networks - New developments in self-organizing maps
Asymptotically optimal block quantization
IEEE Transactions on Information Theory
Asymptotic quantization error of continuous signals and the quantization dimension
IEEE Transactions on Information Theory
Topology preservation in self-organizing feature maps: exact definition and measurement
IEEE Transactions on Neural Networks
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Neural computing modeling of the reference crop evapotranspiration
Environmental Modelling & Software
Improvements on the visualization of clusters in geo-referenced data using Self-Organizing Maps
Computers & Geosciences
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Understanding relationships in high-dimension datasets requires proper data visualization. Two examples of high-dimension data are major-element geochemical and hyperspectral data. Major-element geochemical data consists of eleven oxide measurements for each sample. Well-known correlations exist for these types of data, i.e., the negative relationship between SiO"2 and MgO; other more subtle relationships are rarely apparent. Hyperspectral data is by definition high-dimension data consisting of upwards of 100+ discrete measurements of the electromagnetic spectrum for a material. Hyperspectral data are a significant challenge to interpret when evaluating information for heterogeneous materials such as rocks. Self-organizing maps (SOMs) provide insight into complex relationships in high-dimension datasets while preserving the inherent topological relations and simultaneously producing a statistical model of the dataset. Another benefit of SOMs is their generation of composite vectors which can be analyzed to extract the relative importance of each component during classification. The veracity of SOMs is demonstrated using two datasets from the Spanish peaks intrusive complex of south-central Colorado including major-element geochemical and hyperspectral measurements.