Results 31 to 40 of about 4,584,146 (299)
Applied Sciences, 2021 Brain signals can be measured using multiple imaging modalities, such as magnetic resonance imaging (MRI)-based techniques. Different modalities convey distinct yet complementary information; thus, their joint analyses can provide valuable insight into ...
Chunying Jia +5 more
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Independent Component Analysis for Domain Independent Watermarking [PDF]
, 2002 A new principled domain independent watermarking framework is presented. The new approach is based on embedding the message in statistically independent sources of the covertext to mimimise covertext distortion, maximise the information embedding rate and improve the method's robustness against various attacks.
Stéphane Bounkong +2 more
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Frontiers in Human Neuroscience, 2013 In functional MRI it is desirable for the blood-oxygenation level dependent (BOLD) signal to be localized to the tissue containing activated neurons rather than the veins draining that tissue. This study addresses the dependence of the specificity of the
Alexander eGeissler +12 more
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NeuroImage, 2014 Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult.
G. Khorshidi +5 more
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Binary Independent Component Analysis With or Mixtures [PDF]
IEEE Transactions on Signal Processing, 2011 Independent component analysis (ICA) is a computational method for separating a multivariate signal into subcomponents assuming the mutual statistical independence of the non-Gaussian source signals. The classical Independent Components Analysis (ICA) framework usually assumes linear combinations of independent sources over the field of realvalued ...
Huy Nguyen 0002, Rong Zheng 0001
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Faster Independent Component Analysis by Preconditioning With Hessian Approximations [PDF]
IEEE Transactions on Signal Processing, 2017 Independent Component Analysis (ICA) is a technique for unsupervised exploration of multichannel data that is widely used in observational sciences.
Pierre Ablin +2 more
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TFT-LCD Mura Defects Using Independent Component Analysis
Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2009 Independent component analysis (ICA) is used to detect the mura regions with varying sizes and brightness levels before thresholding, then individually analyzed the mura regions in order to avoid unnecessary background effect.
Shang Liang CHEN, Chi Chin YANG
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Heavy-Tailed Independent Component Analysis [PDF]
2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 2015 Independent component analysis (ICA) is the problem of efficiently recovering a matrix $A \in \mathbb{R}^{n\times n}$ from i.i.d. observations of $X=AS$ where $S \in \mathbb{R}^n$ is a random vector with mutually independent coordinates. This problem has been intensively studied, but all existing efficient algorithms with provable guarantees require ...
Joseph Anderson +3 more
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An Introduction to Independent Component Analysis: InfoMax and FastICA algorithms [PDF]
Tutorials in Quantitative Methods for Psychology, 2010 This paper presents an introduction to independent component analysis (ICA). Unlike principal component analysis, which is based on the assumptions of uncorrelatedness and normality, ICA is rooted in the assumption of statistical independence ...
Dominique Gosselin +2 more
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Bi-Smoothed Functional Independent Component Analysis for EEG Artifact Removal
Mathematics, 2021 Motivated by mapping adverse artifactual events caused by body movements in electroencephalographic (EEG) signals, we present a functional independent component analysis based on the spectral decomposition of the kurtosis operator of a smoothed principal
Marc Vidal +2 more
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