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Informed Source Separation: A Bayesian TutorialSource separation problems are ubiquitous in the physical sciences; any situation where signals are superimposed calls for source separation to estimate the original signals. In h s tutorial I will discuss the Bayesian approach to the source separation problem. This approach has a specific advantage in that it requires the designer to explicitly describe the signal model in addition to any other information or assumptions that go into the problem description. This leads naturally to the idea of informed source separation, where the algorithm design incorporates relevant information about the specific problem. This approach promises to enable researchers to design their own high-quality algorithms that are specifically tailored to the problem at hand.
Document ID
20060019241
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Knuth, Kevin H. (NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
September 7, 2013
Publication Date
January 1, 2005
Subject Category
Numerical Analysis
Meeting Information
Meeting: European Signal Processing Conference (EUSIPCO) 2005
Location: Antalya
Country: Turkey
Start Date: September 4, 2005
End Date: September 8, 2005
Funding Number(s)
CONTRACT_GRANT: AIST-QRS-04-3010
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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