The ICA Data Analysis
Using ICA for analysis of seismic events
... – ICA model was used to examine whether rotational or tilt trends were embedded within the 3 ...the data which will separate any other trends within the available ...
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Data-driven re-referencing of intracranial EEG based on independent component analysis (ICA)
... compared ICA to a bipolar referencing scheme using only three ...real data but avoided signal spread or other unwanted statistical ...channel data in isolation will present a challenging scenario for ...
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POPULATION FUNCTIONAL DATA ANALYSIS OF GROUP ICA-BASED CONNECTIVITY MEASURES FROM fMRI
... noise-free ICA model specifies X = AS, where X is the data matrix (usually dimension reduced by an SVD), rows of S con- tain the non-Gaussian independent components and A is a linear mixing ...matrix. ...
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ICA, Kernel Methods and Nonnegativity: New Paradigms for Dynamical Component Analysis of fMRI Data
... Exploratory data–driven techniques or Blind Source Separation (BSS) methods in fMRI data analysis are neither based on explicit signal models nor on the a priori knowledge of the underlying ...
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Handling of incomplete data sets using ICA and SOM in data mining
... statistical analysis, data min- ing is aimed at finding unsuspected relationships which are of value to the database owners or data ...of data, traditional methods cannot satisfy the need of ...
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ACEAT-493 Data Visualization by PCA, LDA, and ICA
... high-dimensional data into lower-dimensional subspace: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are linear mappings for the usage of ...Component Analysis ...
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Overlearning in marginal distribution-based ICA: analysis and solutions
... On the other hand, it is no more clear that the components corresponding to the largest eigen- values should be the ones to be kept. This leads to a combinatorial problem. Some criterion could be made to choose the right ...
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Independent component ordering in ICA time series analysis
... component analysis (ICA) has provided a new tool to analyze time series, which also gives rise to a question * how to order independent components? In the literature, some methods (Back and Trappenberg, ...
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Functional MRI analysis by a novel spatiotemporal ICA algorithm
... Spatiotemporal data analysis in contrast to the more common methods of either spatial or temporal analysis tries to achieve both spatial and temporal separa- tion by optimizing a joint energy ...
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Temporally constrained ICA with threshold and its application to fMRI data
... fMRI data, the tem- poral reference is usually derived from the convolution of the task paradigm with the ideal ...fMRI data, the inaccuracy of temporal reference will not have much impact on the ...
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ICA-based EEG denoising: a comparative analysis of fifteen methods
... that ICA is an efficient approach for the blind extraction of components of interest from a noisy mixture of ...of ICA to the extraction of epileptic signals in the presence of muscular activities is still ...
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A Constrained ICA-EMD Model for Group Level fMRI Analysis
... of ICA and the formation of subject-specific ...series analysis in functional MRI ( Qian et ...MRI data, representing characteristic resting- state ...
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Independent components analysis (ICA) at the "cocktail-party" in analytical chemistry
... ICA was applied as a statistical approach in the development of an innovative analytical methodology to uncover the most common adulterations and quality deviations of honey [ 32 ...the ICA modeling, two ...
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Independent Comparative Study of PCA, ICA, and LDA on the FERET Data Set
... Key words: face recognition; PCA; ICA; LDA; FERET; subspace analysis methods I. INTRODUCTION Over the last ten years or so, face recognition has become a popular area of research in computer vision and one ...
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Comparative Analysis of ANN-ICA and ANN-GWO for Crop Yield Prediction
... Therefore, the current study aims to find the most proper machine learning for crop yield prediction. To do so, a comparison study conducted to evaluate the performance of two hybrid machine learning methods artificial ...
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The ICA-AtoM Project and Technology
... technical analysis of existing open-source software applications to determine whether we could simply extend these types of applications to meet the needs of the ICA-AtoM ...their data models, which ...
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Basis Decomposition Discriminant ICA
... MST data allowed to us to understand in a much deeper sense the structure behind the fMRI data, and we think that the exposition of this analysis could also help the reader to get more familiar with ...
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Analysis of dual channel ICA based blocking matrix for improved noise estimation
... Under realistic acoustic conditions, prior information is often exploited for practical realizations of supervised and unsupervised signal extraction approaches. This leads to the class of informed signal processing ...
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Functional Subdivision of Group-ICA Results of fMRI Data Collected during Cinema Viewing
... Copyright: ß 2012 Pamilo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, ...
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ICA decomposition and component analysis
... EEGLAB Workshop III, Nov 15-18, 2006, Singapore: Julie Onton – Data Decomposition with ICA 30 Data (all channels). Data Envelope (max min)[r] ...
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