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Independent component analysis: An introduction [PDF]
Applied 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
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Kernel independent component analysis [PDF]
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2004 Summary: We present a class of algorithms for independent component analysis (ICA) which use contrast functions based on canonical correlations in a reproducing kernel Hilbert space. On the one hand, we show that our contrast functions are related to mutual information and have desirable mathematical properties as measures of statistical dependence. On
Francis R. Bach, Michael I. Jordan
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Nonlinear independent component analysis for principled disentanglement in unsupervised deep learning. [PDF]
Patterns (N Y), 2023 Summary A central problem in unsupervised deep learning is how to find useful representations of high-dimensional data, sometimes called “disentanglement.” Most approaches are heuristic and lack a proper theoretical foundation.
Hyvärinen A, Khemakhem I, Morioka H.
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Independent Component Analysis with Functional Neuroscience Data Analysis [PDF]
Journal 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
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Independent component analysis algorithms for non-invasive fetal electrocardiography. [PDF]
PLoS 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
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Independent component analysis in spiking neurons. [PDF]
PLoS Computational Biology, 2010 Although models based on independent component analysis (ICA) have been successful in explaining various properties of sensory coding in the cortex, it remains unclear how networks of spiking neurons using realistic plasticity rules can realize such ...
Cristina Savin +2 more
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robustica: customizable robust independent component analysis [PDF]
BMC 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
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Independent nonlinear component analysis [PDF]
Journal 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
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NeuroImage, 2018 &NA; Independent Component Analysis (ICA) has proven to be an effective data driven method for analyzing EEG data, separating signals from temporally and functionally independent brain and non‐brain source processes and thereby increasing their ...
Arnaud Delorme +2 more
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Independent component analysis: algorithms and applications
Neural Networks, 2000 Aapo Johannes Hyvarinen, Erkki Oja
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