Dependent component analysis for cosmology: a case study
Kuruoglu E. E.
Learning Numerical Linear Algebra. Linear systems (direct and iterative methods) Physical Sciences and Engineering. Astronomy 85A35 Statistical astronomy 68Q32 Computational learning theory
In this paper, we discuss various dependent component analysis approaches available in the literature and study their performances on the problem of separation of dependent cosmological sources from multichannel microwave radiation maps of the sky. Realisticaly simulated cosmological radiation maps are utilised in the simulations which demonstrate the superior performance obtained by tree-dependent component analysis and correlated component analysis methods when compared to classical ICA.
Source: LVA/ICA 2010 - Latent Variable Analysis and Signal Separation. 9th International Conference, pp. 538–545, St. Malo, France, 27-30 September 2010
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@inproceedings{oai:it.cnr:prodotti:44364,
title = {Dependent component analysis for cosmology: a case study},
author = {Kuruoglu E. E.},
doi = {10.1007/978-3-642-15995-4_67},
booktitle = {LVA/ICA 2010 - Latent Variable Analysis and Signal Separation. 9th International Conference, pp. 538–545, St. Malo, France, 27-30 September 2010},
year = {2010}
}
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