The Matrix Computation Toolbox is a collection of MATLAB M-files containing functions for constructing test matrices, computing matrix factorizations, visualizing matrices, and carrying out direct search optimization. Various other miscellaneous functions are also included. This toolbox supersedes the author’s earlier Test Matrix Toolbox (final release 1995). The toolbox was developed in conjunction with the book Accuracy and Stability of Numerical Algorithms (SIAM, Second edition, August 2002, xxx+680 pp.). That book is the primary documentation for the toolbox: it describes much of the underlying mathematics and many of the algorithms and matrices (it also describes many of the matrices provided by MATLAB’s gallery function).

References in zbMATH (referenced in 1177 articles )

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  1. Al-Mohy, Awad H.: A truncated Taylor series algorithm for computing the action of trigonometric and hyperbolic matrix functions (2018)
  2. Antoñana, Mikel; Makazaga, Joseba; Murua, Ander: Efficient implementation of symplectic implicit Runge-Kutta schemes with simplified Newton iterations (2018)
  3. Antoñana, Mikel; Makazaga, Joseba; Murua, Ander: New integration methods for perturbed ODEs based on symplectic implicit Runge-Kutta schemes with application to solar system simulations (2018)
  4. Aston, John A. D.; Kirch, Claudia: High dimensional efficiency with applications to change point tests (2018)
  5. Aurentz, Jared L.; Mach, Thomas; Robol, Leonardo; Vandebril, Raf; Watkins, David S.: Fast and backward stable computation of roots of polynomials. II: Backward error analysis; companion matrix and companion pencil (2018)
  6. Bremer, James: An algorithm for the numerical evaluation of the associated Legendre functions that runs in time independent of degree and order (2018)
  7. Bujanović, Zvonimir; Karlsson, Lars; Kressner, Daniel: A Householder-based algorithm for Hessenberg-triangular reduction (2018)
  8. Carson, Erin; Higham, Nicholas J.: Accelerating the solution of linear systems by iterative refinement in three precisions (2018)
  9. Coelho, Diego F. G.; Dimitrov, Vassil S.; Rakai, L.: Efficient computation of tridiagonal matrices largest eigenvalue (2018)
  10. Cools, Siegfried; Yetkin, Emrullah Fatih; Agullo, Emmanuel; Giraud, Luc; Vanroose, Wim: Analyzing the effect of local rounding error propagation on the maximal attainable accuracy of the pipelined conjugate gradient method (2018)
  11. Coutinho, S. C.: Bounding the degree of solutions of differential equations (2018)
  12. D’Amore, Luisa; Mele, Valeria; Campagna, Rosanna: Quality assurance of Gaver’s formula for multi-precision Laplace transform inversion in real case (2018)
  13. D’Amore, Luisa; Romano, Diego: An objective criterion for stopping light-surface interaction. Numerical validation and quality assessment (2018)
  14. Defez, Emilio; Ibáñez, Javier; Sastre, Jorge; Peinado, Jesús; Alonso, Pedro: A new efficient and accurate spline algorithm for the matrix exponential computation (2018)
  15. Dey, Papri; Pillai, Harish K.: A complete characterization of determinantal quadratic polynomials (2018)
  16. Diao, Huai-An; Liang, Liming; Qiao, Sanzheng: A condition analysis of the weighted linear least squares problem using dual norms (2018)
  17. Diao, Huai-An; Sun, Yang: Mixed and componentwise condition numbers for a linear function of the solution of the total least squares problem (2018)
  18. Dmytryshyn, Andrii; Dopico, Froilán M.: Generic skew-symmetric matrix polynomials with fixed rank and fixed odd grade (2018)
  19. Falcão, M. Irene; Miranda, Fernando; Severino, Ricardo; Soares, M. Joana: Evaluation schemes in the ring of quaternionic polynomials (2018)
  20. Fasi, Massimiliano; Higham, Nicholas J.: Multiprecision algorithms for computing the matrix logarithm (2018)

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