Nonlinear dimensionality reduction methods in climate data analysis
Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality. These hnear methods may not be appropriate for the analysis of data arising from nonlinear processes...
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University of Bristol
2008
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492479 |