Orthogonal approach to independent component analysis using quaternionic factorization
Abstract Independent component analysis (ICA) is a popular technique for demixing multichannel data. The performance of a typical ICA algorithm strongly depends on the presence of additive noise, the actual distribution of source signals, and the estimated number of non-Gaussian components. Often, a...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2020-09-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
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| Online Access: | http://link.springer.com/article/10.1186/s13634-020-00697-0 |