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Latest revision as of 12:15, 12 October 2023 edit undoTom.Reding (talk | contribs)Autopatrolled, Extended confirmed users, Page movers, Template editors3,944,035 editsm +{{Redirect category shell}}Tag: AWB |
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'''Blind signal separation''', also known as '''blind source separation''', is the separation of a set of source ] from a set of mixed signals, without the aid of information (or with very little information) about the source signals or the mixing process. This problem is in general highly ], but useful solutions can be derived under a surprising variety of conditions. Much of the early literature in this field focuses on the separation of temporal signals such as audio. However, blind signal separation is now routinely performed on ], such as ] and ], which may involve no time dimension whatsoever. |
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==Approaches== |
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Since the chief difficulty of the problem is its underdetermination, methods for blind source separation generally seek to narrow the set of possible solutions in a way that is unlikely to exclude the desired solution. In one approach, exemplified by ] and ] component analysis, one seeks source signals that are minimally ] or maximally ] in a probabilistic or ] sense. A second approach, exemplified by ], is to impose structural constraints on the source signals. These structural constraints may be derived from a generative model of the signal, but are more commonly heuristics justified by good empirical performance. A common theme in the second approach is to impose some kind of low-complexity constraint on the signal, such as ] in some ] for the signal space. This approach can be particularly effective if one requires not the whole signal, but merely its most salient features. |
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===Methods=== |
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There are different methods of blind signal separation: |
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== See also == |
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==References== |
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*Ranjan Acharyya (editors) (2008): ''A New Approach for Blind Source Separation of Convolutive Sources'', ISBN 3-639-07797-0 ISBN 978-3639077971 |
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== External links == |
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{{Commons category|Blind signal separation}} |
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{{signal-processing-stub}} |
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