Abstract: The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, ...
USACE's Buffalo District uses matrix teams to unite diverse roles and expertise, delivering solutions for the nation’s toughest infrastructure challenges.
Abstract: Linear discriminant analysis (LDA) is a widely used technique for data classification. The method offers adequate performance in many classification problems, but it becomes inefficient when ...
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