Unmixing fMRI with independent component analysis.
Independent component analysis (ICA) is a statistical method used to discover hidden factors (sources or features) from a set of measurements or observed data such that the sources are maximally independent. Typically, it assumes a generative model where observations are assumed to be linear mixture...
| 發表在: | IEEE Engineering in medicine and biology magazine 25, 2 (2006). |
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| 格式: | Article |
| 語言: | English |
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