Results 11 to 20 of about 4,584,146 (299)
Identifying Rodent Resting-State Brain Networks with Independent Component Analysis
Frontiers in Neuroscience, 2017 Rodent models have opened the door to a better understanding of the neurobiology of brain disorders and increased our ability to evaluate novel treatments.
Dusica Bajic +12 more
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Function Classes for Identifiable Nonlinear Independent Component Analysis [PDF]
Neural Information Processing Systems, 2022 Unsupervised learning of latent variable models (LVMs) is widely used to represent data in machine learning. When such models reflect the ground truth factors and the mechanisms mapping them to observations, there is reason to expect that they allow ...
Simon Buchholz +2 more
semanticscholar +1 more source
Independent Component Analysis
Encyclopedia of Biometrics, 2001 Aapo Hyvärinen +2 more
semanticscholar +3 more sources
BOTNET DETECTION USING INDEPENDENT COMPONENT ANALYSIS
International Islamic University Malaysia Engineering Journal, 2022 Botnet is a significant cyber threat that continues to evolve. Botmasters continue to improve the security framework strategy for botnets to go undetected.
Wan Nurhidayah Ibrahim +3 more
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Topographic Independent Component Analysis [PDF]
Neural Computation, 2001 In ordinary independent component analysis, the components are assumed to be completely independent, and they do not necessarily have any meaningful order relationships. In practice, however, the estimated “independent” components are often not at all independent. We propose that this residual dependence structure could be used to define a topo-graphic
Aapo Hyvärinen +2 more
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Randomized independent component analysis [PDF]
2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE), 2016 Independent component analysis (ICA) is a method for recovering statistically independent signals from observations of unknown linear combinations of the sources. Some of the most accurate ICA decomposition methods require searching for the inverse transformation which minimizes different approximations of the Mutual Information, a measure of ...
Matan Sela, Ron Kimmel
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Applied Sciences, 2021 Dimensional reduction methods have significantly improved the simplification of Pulsed Thermography (PT) data while improving the accuracy of the results. Such approaches reduce the quantity of data to analyze and improve the contrast of the main defects
Julien R. Fleuret +3 more
doaj +1 more source
Time-Lagged Independent Component Analysis of Random Walks and Protein Dynamics
bioRxiv, 2021 Time-lagged independent component analysis (tICA) is a widely used dimension reduction method for the analysis of molecular dynamics (MD) trajectories and has proven particularly useful for the construction of protein dynamics Markov models.
Steffen Schultze, H. Grubmüller
semanticscholar +1 more source
Optimal dimensionality selection for independent component analysis of transcriptomic data
BMC Bioinformatics, 2021 Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals.
John Luke McConn +4 more
semanticscholar +1 more source
Non-Contact Heart Sound Measurement Using Independent Component Analysis
IEEE Access, 2022 A non-contact heart sound measurement method using independent component analysis (ICA) was successfully developed, and the measured heart sound was quantitatively evaluated with the signal-to-noise ratio (SNR). There have been recent developments in the
Shun Muramatsu +3 more
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