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 259 articles , 2 standard articles )

Showing results 1 to 20 of 259.
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  1. Aiton, Kevin W.; Driscoll, Tobin A.: An adaptive partition of unity method for multivariate Chebyshev polynomial approximations (2019)
  2. Aurentz, Jared L.; Austin, Anthony P.; Benzi, Michele; Kalantzis, Vassilis: Stable computation of generalized matrix functions via polynomial interpolation (2019)
  3. Brugnano, Luigi; Gurioli, Gianmarco; Sun, Yajuan: Energy-conserving Hamiltonian boundary value methods for the numerical solution of the Korteweg-de Vries equation (2019)
  4. Filip, Silviu; Javeed, Aurya; Trefethen, Lloyd N.: Smooth random functions, random ODEs, and Gaussian processes (2019)
  5. Glau, Kathrin; Mahlstedt, Mirco; Pötz, Christian: A new approach for American option pricing: the dynamic Chebyshev method (2019)
  6. Houska, Boris; Chachuat, Benoît: Global optimization in Hilbert space (2019)
  7. Lambers, James V.; Sumner, Amber C.: Explorations in numerical analysis (2019)
  8. Li, Min; Huang, Chengming: The linear barycentric rational quadrature method for auto-convolution Volterra integral equations (2019)
  9. Mortari, Daniele; Johnston, Hunter; Smith, Lidia: High accuracy least-squares solutions of nonlinear differential equations (2019)
  10. Paganini, Alberto; Sturm, Kevin: Weakly normal basis vector fields in RKHS with an application to shape Newton methods (2019)
  11. Papp, Dávid; Yildiz, Sercan: Sum-of-squares optimization without semidefinite programming (2019)
  12. Piazzon, Federico: Pluripotential numerics (2019)
  13. Raissi, M.; Perdikaris, P.; Karniadakis, G. E.: Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations (2019)
  14. Abdi, Ali; Berrut, Jean-Paul; Hosseini, Seyyed Ahmad: The linear barycentric rational method for a class of delay Volterra integro-differential equations (2018)
  15. Abdi, Ali; Hosseini, Seyyed Ahmad: The barycentric rational difference-quadrature scheme for systems of Volterra integro-differential equations (2018)
  16. Aiton, Kevin W.; Driscoll, Tobin A.: An adaptive partition of unity method for Chebyshev polynomial interpolation (2018)
  17. Ament, Sebastian; O’Neil, Michael: Accurate and efficient numerical calculation of stable densities via optimized quadrature and asymptotics (2018)
  18. Birkisson, Ásgeir: Automatic reformulation of odes to systems of first-order equations (2018)
  19. Boulton, Lyonell; Schroers, Bernd J.; Smedley-Williams, Kim: Quantum bound states in Yang-Mills-Higgs theory (2018)
  20. Fasi, Massimiliano; Iannazzo, Bruno: Computing the weighted geometric mean of two large-scale matrices and its inverse times a vector (2018)

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