advanpix: Multiprecision Computing Toolbox for MATLAB. The Multiprecision Computing Toolbox is the MATLAB extension for computing with arbitrary precision. The toolbox equips MATLAB with a new multiple precision floating-point numeric type and extensive set of mathematical functions that are capable of computing with arbitrary precision. The multiprecision numbers and matrices can be seamlessly used in place of the built-in double entities following standard MATLAB syntax rules. As a result, existing MATLAB programs can be converted to run with arbitrary precision with no (or minimal) changes to source code. Quadruple precision computations (compliant with IEEE 754-2008) are supported as a special case.

References in zbMATH (referenced in 35 articles )

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  1. Cayama, Jorge; Cuesta, Carlota M.; de la Hoz, Francisco: Numerical approximation of the fractional Laplacian on (\mathbbR) using orthogonal families (2020)
  2. Elsworth, Steven; Güttel, Stefan: The block rational Arnoldi method (2020)
  3. Go, Myeong-Seok; Lim, Jae Hyuk; Kim, Jin-Gyun; Hwang, Ki-Ryoung: A family of Craig-Bampton methods considering residual mode compensation (2020)
  4. Hervella-Nieto, Luis; López-Pérez, Paula M.; Prieto, Andrés: Robustness and dispersion analysis of the partition of unity finite element method applied to the Helmholtz equation (2020)
  5. Ogita, Takeshi; Aishima, Kensuke: Iterative refinement for singular value decomposition based on matrix multiplication (2020)
  6. Rump, Siegfried M.: On recurrences converging to the wrong limit in finite precision and some new examples (2020)
  7. Xu, Yiran; Li, Jingye; Chen, Xiaohong; Pang, Guofei: Solving fractional Laplacian visco-acoustic wave equations on complex-geometry domains using Grünwald-formula based radial basis collocation method (2020)
  8. Carbone, Maurizio; Iovieno, Michele: Application of the nonuniform fast Fourier transform to the direct numerical simulation of two-way coupled particle laden flows (2019)
  9. Chen, Zheng; Hauck, Cory D.: Multiscale convergence properties for spectral approximations of a model kinetic equation (2019)
  10. Courtier, N. E.; Foster, J. M.; O’Kane, S. E. J.; Walker, A. B.; Richardson, G.: Systematic derivation of a surface polarisation model for planar perovskite solar cells (2019)
  11. Fornberg, Bengt; Reeger, Jonah A.: An improved Gregory-like method for 1-D quadrature (2019)
  12. Higham, Nicholas J.; Mary, Theo: A new preconditioner that exploits low-rank approximations to factorization error (2019)
  13. Higham, Nicholas J.; Pranesh, Srikara: Simulating low precision floating-point arithmetic (2019)
  14. Ogita, Takeshi; Aishima, Kensuke: Iterative refinement for symmetric eigenvalue decomposition. II. Clustered eigenvalues (2019)
  15. Pollak, Moshe; Shauly-Aharonov, Michal: A double recursion for calculating moments of the truncated normal distribution and its connection to change detection (2019)
  16. Clamond, Didier; Dutykh, Denys: Accurate fast computation of steady two-dimensional surface gravity waves in arbitrary depth (2018)
  17. Fasi, Massimiliano; Higham, Nicholas J.: Multiprecision algorithms for computing the matrix logarithm (2018)
  18. Lin, Weilu; Wang, Zejian; Huang, Mingzhi; Zhuang, Yingping; Zhang, Siliang: On structural identifiability analysis of the cascaded linear dynamic systems in isotopically non-stationary 13C labelling experiments (2018)
  19. Ogita, Takeshi; Aishima, Kensuke: Iterative refinement for symmetric eigenvalue decomposition (2018)
  20. Pan, Binfeng; Wang, Yang; Tian, Shaohua: A high-precision single shooting method for solving hypersensitive optimal control problems (2018)

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