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- Joint_Approximation_Diagonalization_of_Eigen-matrices abstract "Joint Approximation Diagonalization of Eigen-matrices (JADE) is an algorithm for independent component analysis that separates observed mixed signals into latent source signals by exploiting fourth order moments. The fourth order moments are a measure of non-Gaussianity, which is used as a proxy for defining independence between the source signals. The motivation for this measure is that Gaussian distributions possess zero excess kurtosis, and with non-Gaussianity being a canonical assumption of ICA, JADE seeks an orthogonal rotation of the observed mixed vectors to estimate source vectors which possess high values of excess kurtosis.".
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageID "48210391".
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageLength "2309".
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageOutDegree "6".
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageRevisionID "698495730".
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageWikiLink Category:Statistics.
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageWikiLink Independent_component_analysis.
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageWikiLink Kurtosis.
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageWikiLink Latent_variable.
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageWikiLink Moment_(mathematics).
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageWikiLinkText "Joint Approximation Diagonalization of Eigen-matrices".
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageUsesTemplate Template:Reflist.
- Joint_Approximation_Diagonalization_of_Eigen-matrices wikiPageUsesTemplate Template:Statistics-stub.
- Joint_Approximation_Diagonalization_of_Eigen-matrices subject Category:Statistics.
- Joint_Approximation_Diagonalization_of_Eigen-matrices hypernym Algorithm.
- Joint_Approximation_Diagonalization_of_Eigen-matrices type Software.
- Joint_Approximation_Diagonalization_of_Eigen-matrices comment "Joint Approximation Diagonalization of Eigen-matrices (JADE) is an algorithm for independent component analysis that separates observed mixed signals into latent source signals by exploiting fourth order moments. The fourth order moments are a measure of non-Gaussianity, which is used as a proxy for defining independence between the source signals.".
- Joint_Approximation_Diagonalization_of_Eigen-matrices label "Joint Approximation Diagonalization of Eigen-matrices".
- Joint_Approximation_Diagonalization_of_Eigen-matrices wasDerivedFrom Joint_Approximation_Diagonalization_of_Eigen-matrices?oldid=698495730.
- Joint_Approximation_Diagonalization_of_Eigen-matrices isPrimaryTopicOf Joint_Approximation_Diagonalization_of_Eigen-matrices.