= Joint Approximation Diagonalization of Eigen-matrices
{wiki=Joint_Approximation_Diagonalization_of_Eigen-matrices}
Joint Approximation Diagonalization of Eigen-matrices (JADE) is a mathematical technique used primarily in the fields of blind source separation, independent component analysis, and signal processing. This method arises from the desire to simultaneously diagonalize several matrices, which typically represent second-order statistics of different signals or datasets.
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