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- W1617998161 abstract "We describe a model where an independent component problem and a related linear inverse problem are modelled simultaneously, and construct an algorithm which in some circumstances produces demixing matrices of better quality than the basic ICA algorithms. The effect is achieved by adding a penalty term, motivated by the inverse problem, to the ICA objective function. Our method is related to the idea, which has received some attention in the brain imaging context, that solutions of independent component problems can be used as a basis for inverse methods." @default.
- W1617998161 created "2016-06-24" @default.
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- W1617998161 date "2015-07-01" @default.
- W1617998161 modified "2023-09-27" @default.
- W1617998161 title "Independent component analysis with an inverse problem motivated penalty term" @default.
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- W1617998161 doi "https://doi.org/10.1109/ijcnn.2015.7280650" @default.
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