Classification and analysis of emission-line galaxies using mean field independent component analysis [PDF]
, 2013 We present an analysis of the optical spectra of narrow emission-line galaxies, based on mean field independent component analysis (MFICA). Samples of galaxies were drawn from the Sloan Digital Sky Survey (SDSS) and used to generate compact sets of ...
Allen, James T. +4 more
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Application of independent component analysis to Fermilab Booster
Physical Review Special Topics. Accelerators and Beams, 2005 Autocorrelation is applied to analyze sets of finite-sampling data such as the turn-by-turn beam position monitor (BPM) data in an accelerator. This method of data analysis, called the independent component analysis (ICA), is shown to be a powerful beam ...
Xiaobiao Huang +3 more
doaj +1 more source
A Constrained EM Algorithm for Independent Component Analysis [PDF]
, 2001 We introduce a novel way of performing independent component analysis using a constrained version of the expectation-maximization (EM) algorithm. The source distributions are modeled as D one-dimensional mixtures of gaussians.
Weber, Markus, Welling, Max
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Independent component approach to the analysis of EEG and MEG recordings [PDF]
, 2000 Multichannel recordings of the electromagnetic fields emerging from neural currents in the brain generate large amounts of data. Suitable feature extraction methods are, therefore, useful to facilitate the representation and interpretation of the data ...
Hämäläinen, Dr Matti +4 more
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Meta-Analysis of Esophageal Cancer Transcriptomes Using Independent Component Analysis
Frontiers in Genetics, 2021 Independent Component Analysis is a matrix factorization method for data dimension reduction. ICA has been widely applied for the analysis of transcriptomic data for blind separation of biological, environmental, and technical factors affecting gene ...
Ainur Ashenova +7 more
doaj +1 more source
Background Subtraction Approach Based on Independent Component Analysis
Sensors, 2010 In this work, a new approach to background subtraction based on independent component analysis is presented. This approach assumes that background and foreground information are mixed in a given sequence of images.
Hugo Jiménez-Hernández
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aNy-way Independent Component Analysis [PDF]
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020 AbstractMultimodal data fusion is a topic of great interest. Several fusion methods have been proposed to investigate coherent patterns and corresponding linkages across modalities, such as joint independent component analysis (jICA), multiset canonical correlation analysis (mCCA), mCCA+jICA, disjoint subspace using ICA (DS-ICA) and parallel ICA.
Duan, Kuaikuai +3 more
openaire +3 more sources
Independent component analysis: algorithms and applications [PDF]
, 2000 A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors.
A. Hyvärinen, E. Oja
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Complex Independent Component Analysis of Frequency-Domain Electroencephalographic Data
, 2003 Independent component analysis (ICA) has proven useful for modeling brain and electroencephalographic (EEG) data. Here, we present a new, generalized method to better capture the dynamics of brain signals than previous ICA algorithms.
Amari +24 more
core +5 more sources
Assessing material densities by vibration analysis and independent component analysis [PDF]
, 2013 The aim of this study was to investigate vibration analysis and independent component analysis (ICA) to assess the density of multiple materials making up a single structure.
Bishop, Nick +5 more
core +1 more source