Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

Exploratory analysis of climate data using source separation methods

The goal of this research project is to use novel machine learning techniques such as independent component analysis (ICA) and more general denoising source separation (DSS) for extracting significant patterns of global climate variability.


Group members

You are at: CIS → Source separation methods for climate data analysis

Page maintained by webmaster at, last updated Wednesday, 07-Oct-2009 12:12:47 EEST