In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents....

principal components analysis Component analysis (statistics), any analysis of two or more independent variables Connected-component analysis, in graph theory...

Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...

models, such as multilinear principal component analysis (MPCA) or multilinear independent component analysis (MICA). The origin of MPCA can be traced...

kernel-independent component analysis (kernel ICA) is an efficient algorithm for independent component analysis which estimates source components by optimizing...

principal component analysis (PCA), independent component analysis (ICA), linear discriminant analysis (LDA) and canonical correlation analysis (CCA). Multilinear...

points in the dataset. Examples include dictionary learning, independent component analysis, matrix factorization, and various forms of clustering. In self-supervised...

of the more successful approaches are principal components analysis and independent component analysis, which work well when there are no delays or echoes...

Dependent component analysis (DCA) is a blind signal separation (BSS) method and an extension of Independent component analysis (ICA). ICA is the separating...

element analysis – a computer simulation technique used in engineering analysis Independent component analysis Link quality analysis – the analysis of signal...

methods of analysis focus either on independent components or on regions of correlation.[citation needed] Independent component analysis (ICA) is a useful...

Information Science Ruye Wang, Independent Component Analysis, node4: Measures of Non-Gaussianity P. Comon, Independent Component Analysis – a new concept?, Signal...

etc. Independent component analysis (ICA) is another signal processing solution that separates different signals that are statistically independent in time...

FastICA is an efficient and popular algorithm for independent component analysis invented by Aapo Hyvärinen at Helsinki University of Technology. Like...

robust effect of finding the DMN with resting-state scans and independent component analysis (ICA). Another reason was that the DMN could be measured with...

transformation, k-means produces the solution to the linear independent component analysis (ICA) task. This aids in explaining the successful application...

Formal concept analysis Independent component analysis Non-negative matrix factorization Q methodology Recommendation system Root cause analysis Facet theory...

factorizations methods such as TensorFaces and multilinear (tensor) independent component analysis factorizes the data tensor into a set of vector spaces that...

considered at a particular level of analysis Lumped element model, a model of spatially distributed systems Component video, a type of analog video information...

world data sets consist of data vectors whose individual components are not statistically independent. In other words, knowing the value of an element will...

when neural networks implement a form of Principal Component Analysis or Independent Component Analysis. A "clustering" is essentially a set of such clusters...

detectable through independent component analysis of resting state fMRI images, as well as seed based functional connectivity analysis. The functional connectivity...

networks may be found using algorithms such as cluster analysis, spatial independent component analysis (ICA), seed based, and others. Synchronized brain regions...

His postdoc, Tony Bell, developed the infomax algorithm for Independent Component Analysis (ICA) which has been widely adopted in machine learning, signal...

Component analysis is the analysis of two or more independent variables which comprise a treatment modality. It is also known as a dismantling study....

multivariate statistics, kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods...

the basic processing tools, EEGLAB implements independent component analysis (ICA), time/frequency analysis, artifact rejection, and several modes of data...

(Putna Întunecoasă), also known as the Tica River Temporal independent component analysis (tICA) The feminine form of Tico, slang for a native of Costa...

science/engineering applications, such as independent component analysis, image analysis, genetic analysis, speech recognition, manifold learning, and...

Hierarchical ensembles based on Gabor Fisher classifier and independent component analysis preprocessing techniques are some of the earliest ensembles...