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 1142 articles )

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  1. Carson, Erin; Higham, Nicholas J.: Accelerating the solution of linear systems by iterative refinement in three precisions (2018)
  2. Coelho, Diego F.G.; Dimitrov, Vassil S.; Rakai, L.: Efficient computation of tridiagonal matrices largest eigenvalue (2018)
  3. 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)
  4. D’Amore, Luisa; Romano, Diego: An objective criterion for stopping light-surface interaction. Numerical validation and quality assessment (2018)
  5. Dey, Papri; Pillai, Harish K.: A complete characterization of determinantal quadratic polynomials (2018)
  6. Dmytryshyn, Andrii; Dopico, Froilán M.: Generic skew-symmetric matrix polynomials with fixed rank and fixed odd grade (2018)
  7. Fasi, Massimiliano; Higham, Nicholas J.: Multiprecision algorithms for computing the matrix logarithm (2018)
  8. Gu, Xian-Ming; Huang, Ting-Zhu; Yin, Guojian; Carpentieri, Bruno; Wen, Chun; Du, Lei: Restarted Hessenberg method for solving shifted nonsymmetric linear systems (2018)
  9. Hasegawa, Takemitsu; Sugiura, Hiroshi: Uniform approximation to Cauchy principal value integrals with logarithmic singularity (2018)
  10. Jeannerod, Claude-Pierre; Rump, Siegfried M.: On relative errors of floating-point operations: optimal bounds and applications (2018)
  11. Li, Hanyu: Structured condition numbers for some matrix factorizations of structured matrices (2018)
  12. Li, Hanyu; Wang, Shaoxin: On the partial condition numbers for the indefinite least squares problem (2018)
  13. Miyajima, Shinya: Fast verified computation for the matrix principal $p$th root (2018)
  14. Oozawa, Masaya; Sogabe, Tomohiro; Miyatake, Yuto; Zhang, Shao-Liang: On a relationship between the $\operatornameT$-congruence Sylvester equation and the Lyapunov equation (2018)
  15. O’Rourke, Sean; Vu, Van; Wang, Ke: Random perturbation of low rank matrices: improving classical bounds (2018)
  16. Raghunathan, Arvind U.; Biegler, Lorenz T.: $LDL^T$ direction interior point method for semidefinite programming (2018)
  17. Stanimirović, Ivan: Computation of generalized matrix inverses and applications (2018)
  18. Stanimirović, Predrag S.; Srivastava, Shwetabh; Gupta, D.K.: From Zhang neural network to scaled hyperpower iterations (2018)
  19. Ye, Ke; Lim, Lek-Heng: Fast structured matrix computations: tensor rank and Cohn-Umans method (2018)
  20. Zainali, Nahid; Lotfi, Taher: On developing a stable and quadratic convergent method for solving absolute value equation (2018)

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