Daniel Dornbusch, Robert Haschke, Stefan Menzel, Heiko Wersing, "Finding Correlations in Multimodal Data Using Decomposition Approaches", European Symposium on Artificial Neural Networks (ESANN), pp. 253 – 258, 2010.

In this paper, we propose the application of standard decomposition approaches to find local correlations in multimodal data. In a test scenario, we apply these methods to correlate the local shape of turbine blades with their associated aerodynamic flow fields. We compare several decomposition algorithms, i.e., k-Means, Principal Component Analysis, Non-negative Matrix Factorization and Non-Negative Sparse Coding, with regards to their efficiency at finding local correlations and their ability to predict one modality from another.