The Matrix Function Toolbox is a MATLAB toolbox connected with functions of matrices. It is associated with the book Functions of Matrices: Theory and Computation and contains implementations of many of the algorithms described in the book. The book is the main documentation for the toolbox. The toolbox is intended to facilitate understanding of the algorithms through MATLAB experiments, to be useful for research in the subject, and to provide a basis for the development of more sophisticated implementations. The codes are ”plain vanilla” versions; they contain the core algorithmic aspects with a minimum of inessential code. In particular, the following features should be noted. The codes have little error checking of input arguments. The codes do not print intermediate results or the progress of an iteration. For the iterative algorithms a convergence tolerance is hard-coded (in function mft_tolerance). For greater flexibility this tolerance could be made an input argument. The codes are designed for simplicity and readability rather than maximum efficiency. Algorithmic options such as preprocessing are omitted. The codes are intended for double precision matrices. Those algorithms in which the parameters can be adapted to the precision have not been written to take advantage of single precision inputs.

References in zbMATH (referenced in 492 articles , 1 standard article )

Showing results 1 to 20 of 492.
Sorted by year (citations)

1 2 3 ... 23 24 25 next

  1. Jagels, Carl; Jbilou, Khalide; Reichel, Lothar: The extended global Lanczos method, Gauss-Radau quadrature, and matrix function approximation (2021)
  2. Yang, Junjian; Lu, Linzhang: Weighted geometric mean of two accretive matrices (2021)
  3. Abdalla, Mohamed: Special matrix functions: characteristics, achievements and future directions (2020)
  4. Abderramán Marrero, J.; Aiat Hadj, D. A.: Improving formulas for the eigenvalues of finite block-Toeplitz tridiagonal matrices (2020)
  5. Abul-Ez, M.; Abd-Elmageed, H.; Hidan, M.; Abdalla, M.: On the growth order and growth type of entire functions of several complex matrices (2020)
  6. Acebrón, Juan A.: A probabilistic linear solver based on a multilevel Monte Carlo method (2020)
  7. Acebrón, Juan A.; Herrero, José R.; Monteiro, José: A highly parallel algorithm for computing the action of a matrix exponential on a vector based on a multilevel Monte Carlo method (2020)
  8. Ackerer, Damien; Filipović, Damir: Linear credit risk models (2020)
  9. Baake, Michael; Sumner, Jeremy: Notes on Markov embedding (2020)
  10. Bao, Sijia; Constales, Denis; De Bie, Hendrik; Mertens, Teppo: Solutions for the Lévy-Leblond or parabolic Dirac equation and its generalizations (2020)
  11. Barbarino, Giovanni; Garoni, Carlo; Serra-Capizzano, Stefano: Block generalized locally Toeplitz sequences: theory and applications in the multidimensional case (2020)
  12. Bellavia, S.; Donatelli, M.; Riccietti, Elisa: An inexact non stationary Tikhonov procedure for large-scale nonlinear ill-posed problems (2020)
  13. Bentbib, A. H.; El Ghomari, M.; Jbilou, K.: Extended nonsymmetric global Lanczos method for matrix function approximation (2020)
  14. Bertaccini, D.; Durastante, F.: Computing functions of very large matrices with small TT/QTT ranks by quadrature formulas (2020)
  15. Bishop, Adrian N.; Del Moral, Pierre; Niclas, Angèle: A perturbation analysis of stochastic matrix Riccati diffusions (2020)
  16. Casanellas, Marta; Fernández-Sánchez, Jesús; Roca-Lacostena, Jordi: Embeddability and rate identifiability of Kimura 2-parameter matrices (2020)
  17. Čiegis, Raimondas; Vabishchevich, Petr N.: High order numerical schemes for solving fractional powers of elliptic operators (2020)
  18. Espig, Mike; Hackbusch, Wolfgang; Litvinenko, Alexander; Matthies, Hermann G.; Zander, Elmar: Iterative algorithms for the post-processing of high-dimensional data (2020)
  19. Faßbender, Heike; Halwaß, Martin: On the singular value decomposition of (skew-)involutory and (skew-)coninvolutory matrices (2020)
  20. Fika, Paraskevi; Mitrouli, Marilena; Roupa, Paraskevi; Triantafyllou, Dimitrios: The e-MoM approach for approximating matrix functionals (2020)

1 2 3 ... 23 24 25 next