Abstract
This paper summarises our research on the separation of astrophysical source maps from multichannel observations, utilising techniques ranging from fully blind source separation to Bayesian estimation. Each observed map is a mix of various source processes. Separating the individual sources from a set of observed maps is of great importance to astrophysicists. We first tested classical fully blind methods and then developed our approach by adopting generic source models and prior information about the mixing operator. We also exploited a Bayesian formulation to incorporate further prior information into the problem. Our test data sets simulate the ones expected by the forthcoming ESA’s mission Planck Surveyor Satellite mission.
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© 2004 Springer-Verlag Berlin Heidelberg
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Salerno, E., Tonazzini, A., Kuruoğlu, E.E., Bedini, L., Herranz, D., Baccigalupi, C. (2004). Source Separation Techniques Applied to Astrophysical Maps. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30134-9_57
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DOI: https://doi.org/10.1007/978-3-540-30134-9_57
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