@inproceedings {PN18609,
	title = {Finding Correlations in Multimodal Data Using Decomposition Approaches},
	author = {Daniel Dornbusch AND Robert Haschke AND Stefan Menzel AND Heiko Wersing},
	year = {2010},
	abstract = {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.},
	publisher = {d-facto},
	booktitle = {European Symposium on Artificial Neural Networks (ESANN)},
	pages = {253 {\textendash} 258},
	address = {Bruges, Belgium}
}