Performance of complex-valued ICA algorithms for fMRI analysis: Importance of taking full diversity into account
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[1] V. Calhoun,et al. Analysis of complex-valued functional magnetic resonance imaging data: are we just going through a "phase"? , 2012 .
[2] Tülay Adali,et al. Comparison of multi‐subject ICA methods for analysis of fMRI data , 2010, Human brain mapping.
[3] Pierre Comon,et al. Handbook of Blind Source Separation: Independent Component Analysis and Applications , 2010 .
[4] Moon,et al. Estimation of mutual information using kernel density estimators. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[5] J. Kruskal. On the shortest spanning subtree of a graph and the traveling salesman problem , 1956 .
[6] Vince D. Calhoun,et al. Performance of blind source separation algorithms for fMRI analysis using a group ICA method. , 2007, Magnetic resonance imaging.
[7] V. Calhoun,et al. Multisubject Independent Component Analysis of fMRI: A Decade of Intrinsic Networks, Default Mode, and Neurodiagnostic Discovery , 2012, IEEE Reviews in Biomedical Engineering.
[8] Ronald Phlypo,et al. An efficient entropy rate estimator for complex-valued signal processing: Application to ICA , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[9] Vince D. Calhoun,et al. De-noising, phase ambiguity correction and visualization techniques for complex-valued ICA of group fMRI data , 2012, Pattern Recognit..
[10] J. Pekar,et al. A method for making group inferences from functional MRI data using independent component analysis , 2001, Human brain mapping.
[11] Tülay Adali,et al. Estimating the number of independent components for functional magnetic resonance imaging data , 2007, Human brain mapping.
[12] Tülay Adali,et al. IVA and ICA: Use of diversity in independent decompositions , 2012, 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO).
[13] T. Adali,et al. Complex ICA of Brain Imaging Data [Life Sciences] , 2007, IEEE Signal Processing Magazine.
[14] Eric Moreau,et al. Blind Identification and Separation of Complex-Valued Signals: Moreau/Blind Identification and Separation of Complex-Valued Signals , 2013 .
[15] Tülay Adali,et al. Complex Independent Component Analysis by Entropy Bound Minimization , 2010, IEEE Transactions on Circuits and Systems I: Regular Papers.
[16] Vince D. Calhoun,et al. A novel approach for assessing reliability of ICA for FMRI analysis , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[17] Vince D. Calhoun,et al. Complex Infomax: Convergence and Approximation of Infomax with Complex Nonlinearities , 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.
[18] Vince D. Calhoun,et al. ICA of fMRI data: Performance of three ICA algorithms and the importance of taking correlation information into account , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[19] Godfrey Pearlson,et al. An adaptive reflexive processing model of neurocognitive function: supporting evidence from a large scale (n = 100) fMRI study of an auditory oddball task , 2005, NeuroImage.
[20] Vince D. Calhoun,et al. Independent component analysis by complex nonlinearities , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[21] Benedikt Loesch,et al. Cramér-Rao Bound for Circular and Noncircular Complex Independent Component Analysis , 2013, IEEE Transactions on Signal Processing.