Chebfun

Chebfun is a collection of algorithms and a software system in object-oriented MATLAB that extends familiar powerful methods of numerical computation involving numbers to continuous or piecewise-continuous functions. It also implements continuous analogues of linear algebra notions like the QR decomposition and the SVD, and solves ordinary differential equations. The mathematical basis of the system combines tools of Chebyshev expansions, fast Fourier transform, barycentric interpolation, recursive zerofinding, and automatic differentiation. (Source: http://freecode.com/)


References in zbMATH (referenced in 364 articles , 2 standard articles )

Showing results 1 to 20 of 364.
Sorted by year (citations)

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  1. An, Congpei; Wu, Hao-Ning: Tikhonov regularization for polynomial approximation problems in Gauss quadrature points (2021)
  2. Aslani, Kyriaki-Evangelia; Sarris, Ioannis E.: Effect of micromagnetorotation on magnetohydrodynamic Poiseuille micropolar flow: analytical solutions and stability analysis (2021)
  3. Bremer, James; Pang, Qiyuan; Yang, Haizhao: Fast algorithms for the multi-dimensional Jacobi polynomial transform (2021)
  4. Dolgov, Sergey; Kressner, Daniel; Strössner, Christoph: Functional Tucker approximation using Chebyshev interpolation (2021)
  5. Jeffrey S. Oishi, Keaton J. Burns, S. E. Clark, Evan H. Anders, Benjamin P. Brown, Geoffrey M. Vasil, Daniel Lecoanet: eigentools: A Python package for studying differential eigenvalue problems with an emphasis on robustness (2021) not zbMATH
  6. Martinson, W. Duncan; Ninomiya, Hirokazu; Byrne, Helen Mary; Maini, Philip Kumar: Comparative analysis of continuum angiogenesis models (2021)
  7. Mitchell, Tim: Fast interpolation-based globality certificates for computing Kreiss constants and the distance to uncontrollability (2021)
  8. Mourrain, Bernard; Telen, Simon; Van Barel, Marc: Truncated normal forms for solving polynomial systems: generalized and efficient algorithms (2021)
  9. Nakatsukasa, Yuji; Townsend, Alex: Error localization of best (L_1) polynomial approximants (2021)
  10. Peiris, V.; Sharon, N.; Sukhorukova, N.; Ugon, J.: Generalised rational approximation and its application to improve deep learning classifiers (2021)
  11. Revers, Michael: Asymptotics of polynomial interpolation and the Bernstein constants (2021)
  12. Shi, Tianyi; Townsend, Alex: On the compressibility of tensors (2021)
  13. Trefethen, Lloyd N.; Nakatsukasa, Yuji; Weideman, J. A. C.: Exponential node clustering at singularities for rational approximation, quadrature, and PDEs (2021)
  14. van den Bos, L. M. M.; Sanderse, B.: A geometrical interpretation of the addition of nodes to an interpolatory quadrature rule while preserving positive weights (2021)
  15. Van Gorder, Robert A.; Klika, Václav; Krause, Andrew L.: Turing conditions for pattern forming systems on evolving manifolds (2021)
  16. Wang, Haiyong: How much faster does the best polynomial approximation converge than Legendre projection? (2021)
  17. Webb, Marcus; Olver, Sheehan: Spectra of Jacobi operators via connection coefficient matrices (2021)
  18. Yan, David; Pugh, M. C.; Dawson, F. P.: Adaptive time-stepping schemes for the solution of the Poisson-Nernst-Planck equations (2021)
  19. Abdi, Ali; Hosseini, Seyyed Ahmad; Podhaisky, Helmut: Numerical methods based on the Floater-Hormann interpolants for stiff VIEs (2020)
  20. Akshar, Anthony; Bueno Cachadina, Maria Isabel; Kassem, Remy; Mileeva, Daria; Perez, Javier: Linearizations for interpolatory bases -- a comparison: new families of linearizations (2020)

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Further publications can be found at: http://www.chebfun.org/publications/