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Independent Component Analysis with Functional Neuroscience Data Analysis [PDF]

open access: yesJournal of Biomedical Physics and Engineering, 2023
Background: Independent Component Analysis (ICA) is the most common and standard technique used in functional neuroscience data analysis. Objective: In this study, two of the significant functional brain techniques are introduced as a model for ...
Hadeel K Aljobouri
doaj   +2 more sources

Independent component analysis algorithms for non-invasive fetal electrocardiography. [PDF]

open access: yesPLoS ONE, 2023
The independent component analysis (ICA) based methods are among the most prevalent techniques used for non-invasive fetal electrocardiogram (NI-fECG) processing. Often, these methods are combined with other methods, such adaptive algorithms.
Rene Jaros   +5 more
doaj   +3 more sources

robustica: customizable robust independent component analysis [PDF]

open access: yesBMC Bioinformatics, 2022
Background Independent Component Analysis (ICA) allows the dissection of omic datasets into modules that help to interpret global molecular signatures.
Miquel Anglada-Girotto   +3 more
doaj   +2 more sources

Heavy-tailed Independent Component Analysis [PDF]

open access: yes2015 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
Anderson, Joseph   +3 more
core   +2 more sources

Noisy independent component analysis of auto-correlated components [PDF]

open access: yesPhysical Review E, 2017
We present a new method for the separation of superimposed, independent, auto-correlated components from noisy multi-channel measurement. The presented method simultaneously reconstructs and separates the components, taking all channels into account and ...
Enßlin, Torsten A., Knollmüller, Jakob
core   +4 more sources

Independent component analysis: An introduction [PDF]

open access: yesApplied Computing and Informatics, 2021
Independent component analysis (ICA) is a widely-used blind source separation technique. ICA has been applied to many applications. ICA is usually utilized as a black box, without understanding its internal details.
Alaa Tharwat
doaj   +1 more source

BOTNET DETECTION USING INDEPENDENT COMPONENT ANALYSIS

open access: yesInternational 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
doaj   +1 more source

Topographic Independent Component Analysis [PDF]

open access: yesNeural 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
Hyvärinen, Aapo   +2 more
openaire   +3 more sources

Principal independent component analysis [PDF]

open access: yesIEEE Transactions on Neural Networks, 1999
Conventional blind signal separation algorithms do not adopt any asymmetric information of the input sources, thus the convergence point of a single output is always unpredictable. However, in most of the applications, we are usually interested in only one or two of the source signals and prior information is almost always available.
J, Luo, B, Hu, X T, Ling, R W, Liu
openaire   +2 more sources

Independent nonlinear component analysis [PDF]

open access: yesJournal of the American Statistical Association, 2019
The idea of summarizing the information contained in a large number of variables by a small number of "factors" or "principal components" has been broadly adopted in economics and statistics. This paper introduces a generalization of the widely used principal component analysis (PCA) to nonlinear settings, thus providing a new tool for dimension ...
Gunsilius, Florian   +1 more
openaire   +2 more sources

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