Orthogonal polynomials. Computation and approximation. Orthogonal polynomials are a widely used class of mathematical functions that are helpful in the solution of many important technical problems. This book provides, for the first time, a systematic development of computational techniques, including a suite of computer programs in Matlab downloadable from the Internet, to generate orthogonal polynomials of a great variety: OPQ: A MATLAB SUITE OF PROGRAMS FOR GENERATING ORTHOGONAL POLYNOMIALS AND RELATED QUADRATURE RULES.

References in zbMATH (referenced in 365 articles , 1 standard article )

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  1. Jagels, Carl; Jbilou, Khalide; Reichel, Lothar: The extended global Lanczos method, Gauss-Radau quadrature, and matrix function approximation (2021)
  2. Bardenet, Rémi; Flamant, Julien; Chainais, Pierre: On the zeros of the spectrogram of white noise (2020)
  3. Bardenet, Rémi; Hardy, Adrien: Monte Carlo with determinantal point processes (2020)
  4. Burkardt, John; Gunzburger, Max; Zhao, Wenju: High-precision computation of the weak Galerkin methods for the fourth-order problem (2020)
  5. Choi, Hee-Sun; Kim, Jin-Gyun; Doostan, Alireza; Park, K. C.: Acceleration of uncertainty propagation through Lagrange multipliers in partitioned stochastic method (2020)
  6. Costabile, F. A.; Gualtieri, M. I.; Napoli, A.: Matrix calculus-based approach to orthogonal polynomial sequences (2020)
  7. Dominici, Diego: Matrix factorizations and orthogonal polynomials (2020)
  8. Dominici, Diego: Power series expansion of a Hankel determinant (2020)
  9. Foupouagnigni, Mama: An introduction to orthogonal polynomials (2020)
  10. Glaubitz, Jan: Stable high order quadrature rules for scattered data and general weight functions (2020)
  11. Glaubitz, Jan; Öffner, Philipp: Stable discretisations of high-order discontinuous Galerkin methods on equidistant and scattered points (2020)
  12. Guo, Ling; Narayan, Akil; Zhou, Tao: Constructing least-squares polynomial approximations (2020)
  13. Gutleb, Timon S.; Olver, Sheehan: A sparse spectral method for Volterra integral equations using orthogonal polynomials on the triangle (2020)
  14. Hascelik, A. Ihsan: Efficient computation of highly oscillatory Fourier-type integrals with monomial phase functions and Jacobi-type singularities (2020)
  15. Im, Jongho; Morikawa, Kosuke; Ha, Hyung-Tae: A least squares-type density estimator using a polynomial function (2020)
  16. Iserles, Arieh; Webb, Marcus: A family of orthogonal rational functions and other orthogonal systems with a skew-Hermitian differentiation matrix (2020)
  17. Jahanbin, Ramin; Rahman, Sharif: Stochastic isogeometric analysis in linear elasticity (2020)
  18. Karvonen, Toni; Särkkä, Simo: Worst-case optimal approximation with increasingly flat Gaussian kernels (2020)
  19. Kubínová, Marie; Pultarová, Ivana: Block preconditioning of stochastic Galerkin problems: new two-sided guaranteed spectral bounds (2020)
  20. Lee, Dongjin; Rahman, Sharif: Practical uncertainty quantification analysis involving statistically dependent random variables (2020)

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