• In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents....
    49 KB (7,462 words) - 10:49, 27 May 2025
  • Thumbnail for Principal component analysis
    Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...
    117 KB (14,851 words) - 06:44, 17 June 2025
  • principal components analysis Component analysis (statistics), any analysis of two or more independent variables Connected-component analysis, in graph theory...
    1 KB (171 words) - 15:42, 29 December 2020
  • Thumbnail for Multilinear subspace learning
    principal component analysis (PCA), independent component analysis (ICA), linear discriminant analysis (LDA) and canonical correlation analysis (CCA). Multilinear...
    14 KB (1,550 words) - 11:33, 3 May 2025
  • of the more successful approaches are principal components analysis and independent component analysis, which work well when there are no delays or echoes...
    10 KB (1,301 words) - 05:05, 20 May 2025
  • kernel-independent component analysis (kernel ICA) is an efficient algorithm for independent component analysis which estimates source components by optimizing...
    4 KB (516 words) - 03:53, 24 July 2023
  • FastICA (category Factor analysis)
    FastICA is an efficient and popular algorithm for independent component analysis invented by Aapo Hyvärinen at Helsinki University of Technology. Like...
    8 KB (1,239 words) - 13:31, 18 June 2024
  • models, such as multilinear principal component analysis (MPCA) or multilinear independent component analysis (MICA). Tensor rank decomposition were...
    9 KB (974 words) - 00:25, 17 June 2025
  • methods of analysis focus either on independent components or on regions of correlation.[citation needed] Independent component analysis (ICA) is a useful...
    55 KB (6,054 words) - 12:32, 9 January 2025
  • Thumbnail for Feature learning
    points in the dataset. Examples include dictionary learning, independent component analysis, matrix factorization, and various forms of clustering. In self-supervised...
    45 KB (5,114 words) - 02:41, 2 June 2025
  • processing. It is related to network entropy, which is used in independent component analysis. The negentropy of a distribution is equal to the Kullback–Leibler...
    11 KB (1,225 words) - 18:26, 10 June 2025
  • Dependent component analysis (DCA) is a blind signal separation (BSS) method and an extension of Independent component analysis (ICA). ICA is the separating...
    3 KB (461 words) - 13:08, 29 January 2024
  • Thumbnail for Analysis
    element analysis – a computer simulation technique used in engineering analysis Independent component analysis Link quality analysis – the analysis of signal...
    22 KB (2,498 words) - 02:20, 1 June 2025
  • Thumbnail for Magnetoencephalography
    etc. Independent component analysis (ICA) is another signal processing solution that separates different signals that are statistically independent in time...
    42 KB (5,010 words) - 02:33, 2 June 2025
  • Component analysis is the analysis of two or more independent variables which comprise a treatment modality. It is also known as a dismantling study....
    2 KB (204 words) - 02:11, 27 July 2020
  • Thumbnail for Default mode network
    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...
    62 KB (7,080 words) - 23:26, 23 May 2025
  • (Putna Întunecoasă), also known as the Tica River Temporal independent component analysis (tICA) The feminine form of Tico, slang for a native of Costa...
    397 bytes (84 words) - 10:49, 23 March 2019
  • K-means clustering (category Cluster analysis algorithms)
    transformation, k-means produces the solution to the linear independent component analysis (ICA) task. This aids in explaining the successful application...
    62 KB (7,754 words) - 11:44, 13 March 2025
  • Formal concept analysis Independent component analysis Non-negative matrix factorization Q methodology Recommendation system Root cause analysis Facet theory...
    72 KB (10,026 words) - 19:52, 18 June 2025
  • Diagonalization of Eigen-matrices (JADE) is an algorithm for independent component analysis that separates observed mixed signals into latent source signals...
    2 KB (349 words) - 21:27, 25 January 2024
  • His postdoc, Tony Bell, developed the infomax algorithm for Independent Component Analysis (ICA) which has been widely adopted in machine learning, signal...
    21 KB (2,073 words) - 20:58, 22 May 2025
  • factorizations methods such as TensorFaces and multilinear (tensor) independent component analysis factorizes the data tensor into a set of vector spaces that...
    31 KB (4,104 words) - 16:37, 16 June 2025
  • the basic processing tools, EEGLAB implements independent component analysis (ICA), time/frequency analysis, artifact rejection, and several modes of data...
    4 KB (417 words) - 06:09, 14 August 2024
  • Thumbnail for Salience network
    detectable through independent component analysis of resting state fMRI images, as well as seed based functional connectivity analysis. The functional connectivity...
    13 KB (1,452 words) - 23:28, 17 June 2025
  • Thumbnail for Large-scale brain network
    networks may be found using algorithms such as cluster analysis, spatial independent component analysis (ICA), seed based, and others. Synchronized brain regions...
    23 KB (2,394 words) - 13:29, 24 May 2025
  • considered at a particular level of analysis Lumped element model, a model of spatially distributed systems Component video, a type of analog video information...
    2 KB (280 words) - 12:12, 8 November 2024
  • Hierarchical ensembles based on Gabor Fisher classifier and independent component analysis preprocessing techniques are some of the earliest ensembles...
    53 KB (6,685 words) - 14:14, 8 June 2025
  • at the University of Helsinki and known for his research in independent component analysis. Hyvärinen was born in Helsinki and studied mathematics at the...
    3 KB (269 words) - 17:44, 29 November 2024
  • used matrix decomposition techniques include the following: Independent component analysis Semi-discrete decomposition Non-negative matrix factorization...
    26 KB (3,486 words) - 08:03, 22 December 2023
  • Projection pursuit (category Exploratory data analysis)
    used for blind source separation, so it is very important in independent component analysis. Projection pursuit seeks one projection at a time such that...
    4 KB (563 words) - 00:06, 29 March 2025