Non-Iterative Computation of Sparsifiable Solutions to Underdetermined Kronecker Product Linear Systems of Equations

نویسنده

  • Andrew E. Yagle
چکیده

The problem of computing sparse (mostly zero) or sparsifiable (by linear transformation) solutions to underdetermined linear systems of equations has applications in compressed sensing and minimumexposure medical imaging. We present a simple, noniterative, low-computational-cost algorithm for computing a sparse solution to an underdetermined linear system of equations. The system matrix is the Kronecker (tensor) product of two matrices, as in separable 2D deconvolution and reconstruction from partial 2D Fourier data, where the image is sparsifiable by a separable 2D wavelet or other transform. Numerical examples and program illustrate the new algorithm. Keywords— Sparse reconstruction Phone: 734-763-9810. Fax: 734-763-1503. Email: [email protected]. EDICS: 2-REST.

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تاریخ انتشار 2009