UTV

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)


References in zbMATH (referenced in 263 articles , 2 standard articles )

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  1. Caruso, Noè Angelo; Michelangeli, Alessandro; Novati, Paolo: On general convergence behaviours of finite-dimensional approximants for abstract linear inverse problems (2022)
  2. Petkov, Petko H.; Konstantinov, Mihail M.: The numerical Jordan form (2022)
  3. Qin, Junning; Zhong, Hongzhi: A Galerkin time quadrature element formulation for linear structural dynamics (2022)
  4. Abdi, Sarkout; Azizi, Aram; Shafiee, Mahmoud; Saeidian, Jamshid: A numerical method based on three-dimensional Legendre wavelet method for two-dimensional time-fractional diffusion equation (2021)
  5. Duan, Shuyong; Yang, Botao; Wang, Fang; Liu, Guirong: Determination of singular value truncation threshold for regularization in ill-posed problems (2021)
  6. Dziatkiewicz, Grzegorz: New forms of the fundamental solutions for 3D magnetoelectroelasticity equations (2021)
  7. Gratton, S.; Simon, E.; Toint, Ph. L.: An algorithm for the minimization of nonsmooth nonconvex functions using inexact evaluations and its worst-case complexity (2021)
  8. Huang, Jinzhi; Jia, Zhongxiao: On choices of formulations of computing the generalized singular value decomposition of a large matrix pair (2021)
  9. Jia, Zhongxiao; Li, Haibo: The joint bidiagonalization process with partial reorthogonalization (2021)
  10. Luiken, Nick; van Leeuwen, Tristan: Relaxed regularization for linear inverse problems (2021)
  11. Luiken, Nick; van Leeuwen, Tristan: Relaxed regularization for linear inverse problems (2021)
  12. Tavares, Camila A.; Santos, Taináh M. R.; Lemes, Nelson H. T.; dos Santos, José P. C.; Ferreira, José C.; Braga, João P.: Solving ill-posed problems faster using fractional-order Hopfield neural network (2021)
  13. van Lith, Bart S.; Hansen, Per Christian; Hochstenbach, Michiel E.: A twin error gauge for Kaczmarz’s iterations (2021)
  14. van Lith, Bart S.; Hansen, Per Christian; Hochstenbach, Michiel E.: A twin error gauge for Kaczmarz’s iterations (2021)
  15. Voinea-Marinescu, Andreea-Paula; Marin, Liviu; Delvare, Franck: BEM-fading regularization algorithm for Cauchy problems in 2D anisotropic heat conduction (2021)
  16. Zhang, Jianjun; Nagy, James G.: An effective alternating direction method of multipliers for color image restoration (2021)
  17. Zhao, Mingchao; Wen, You-Wei; Ng, Michael; Li, Hongwei: A nonlocal low rank model for Poisson noise removal (2021)
  18. Adcock, Ben; Huybrechs, Daan: Approximating smooth, multivariate functions on irregular domains (2020)
  19. Alvarez, A. C.; Goedert, G. T.; Marchesin, D.: Resonance in rarefaction and shock curves: local analysis and numerics of the continuation method (2020)
  20. Barroso, G.; Seoane, M.; Gil, A. J.; Ledger, P. D.; Mallett, M.; Huerta, A.: A staggered high-dimensional proper generalised decomposition for coupled magneto-mechanical problems with application to MRI scanners (2020)

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