Math @ Duke

Publications [#287187] of Ingrid Daubechies
Papers Published
 Daubechies, I; Roussos, E; Takerkart, S; Benharrosh, M; Golden, C; D'Ardenne, K; Richter, W; Cohen, JD; Haxby, J, Independent component analysis for brain fMRI does not select for independence.,
Proceedings of the National Academy of Sciences of USA, vol. 106 no. 26
(June, 2009),
pp. 1041510422 [19556548], [doi]
(last updated on 2017/12/13)
Abstract: InfoMax and FastICA are the independent component analysis algorithms most used and apparently most effective for brain fMRI. We show that this is linked to their ability to handle effectively sparse components rather than independent components as such. The mathematical design of better analysis tools for brain fMRI should thus emphasize other mathematical characteristics than independence.


dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821
 
Mathematics Department
Duke University, Box 90320
Durham, NC 277080320

