UTV Expansin pack: Special-purpose rank-revealing algorithms This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank-revealing VSV decompositions, we expand the algorithms for the ULLV decomposition of a matrix pair to handle interference-type problems with a rank-deficient covariance matrix, and we provide a robust and reliable Lanczos algorithm which -- despite its simplicity is -- able to capture all the dominant singular values of a sparse or structured matrix. These new algorithms have applications in signal processing, optimization and LSI information retrieval. (Source: http://plato.asu.edu)

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  9. Jia, Zhongxiao; Yang, Yanfei: Modified truncated randomized singular value decomposition (MTRSVD) algorithms for large scale discrete ill-posed problems with general-form regularization (2018)
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  14. Wen, Jin; Cheng, Jun-Feng: The method of fundamental solution for the inverse source problem for the space-fractional diffusion equation (2018)
  15. Zhdanov, Aleksandr Ivanovich: Implicit iterative schemes based on singular decomposition and regularizing algorithms (2018)
  16. Zibetti, Marcelo V. W.; Lin, Chuan; Herman, Gabor T.: Total variation superiorized conjugate gradient method for image reconstruction (2018)
  17. Arcucci, Rossella; D’Amore, Luisa; Pistoia, Jenny; Toumi, Ralf; Murli, Almerico: On the variational data assimilation problem solving and sensitivity analysis (2017)
  18. Bai, Zhong-Zhi; Buccini, Alessandro; Hayami, Ken; Reichel, Lothar; Yin, Jun-Feng; Zheng, Ning: Modulus-based iterative methods for constrained Tikhonov regularization (2017)
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  20. Callahan, Margaret; Calvetti, Daniela; Somersalo, Erkki: Beyond the model limit: parameter inference across scales (2017)

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