GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab. It may also be used as a batch-oriented language. Octave has extensive tools for solving common numerical linear algebra problems, finding the roots of nonlinear equations, integrating ordinary functions, manipulating polynomials, and integrating ordinary differential and differential-algebraic equations. It is easily extensible and customizable via user-defined functions written in Octave’s own language, or using dynamically loaded modules written in C++, C, Fortran, or other languages.

This software is also referenced in ORMS.

References in zbMATH (referenced in 304 articles , 1 standard article )

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  1. Araujo, Leonardo C.; Sansão, João P. H.; Vale-Cardoso, Adriano S.: Fast computation of binomial coefficients (2021)
  2. Araujo, Leonardo C.; Sansão, João P. H.; Vale-Cardoso, Adriano S.: Fast computation of multinomial coefficients (2021)
  3. Cambareri, Pasquale; Di Rienzo, Luca: Complete analytic integrations for the 2D BEM representation of the Laplace equation with linear shape functions (2021)
  4. Curtin, Ryan R.; Edel, Marcus; Prabhu, Rahul Ganesh; Basak, Suryoday; Lou, Zhihao; Sanderson, Conrad: The ensmallen library for flexible numerical optimization (2021)
  5. Dickinson, Peter J. C.; de Zeeuw, Reinier: Generating irreducible copositive matrices using the stable set problem (2021)
  6. Frochte, Jörg: Finite element method. A practical introduction to GNU Octave/MATLAB (2021)
  7. Gilioli, Gianni; Colli, Pierluigi; Colturato, Michele; Gervasio, Paola; Sperandio, Giorgio: A nonlinear model for stage-structured population dynamics with nonlocal density-dependent regulation: an application to the fall armyworm moth (2021)
  8. Jason Rumengan, Terry Yue Zhuo, Conrad Sanderson: PyArmadillo: a streamlined linear algebra library for Python (2021) arXiv
  9. Lie, Knut-Andreas; Møyner, Olav: Advanced Modelling with the MATLAB Reservoir Simulation Toolbox (2021)
  10. Provotar, O. I.; Provotar, O. O.: Approximate calculation of the probability measure of a fuzzy event (2021)
  11. Wipf, Andreas: Statistical approach to quantum field theory. An introduction (2021)
  12. Yaqiong Wang, Francesco Finazzi, Alessandro Fasso: D-STEM v2: A Software for Modeling Functional Spatio-Temporal Data (2021) not zbMATH
  13. Álvarez, Inmaculada C.; Barbero, Javier and Zofío, José L: A Data Envelopment Analysis Toolbox for MATLAB (2020) not zbMATH
  14. Delourme, Bérangère; Duyckaerts, Thomas; Lerner, Nicolas: On integrals over a convex set of the Wigner distribution (2020)
  15. Girardin, Léo: Two components is too simple: an example of oscillatory Fisher-KPP system with three components (2020)
  16. Jan Górecki, Marius Hofert, Martin Holeňa: Hierarchical Archimedean Copulas for MATLAB and Octave: The HACopula Toolbox (2020) not zbMATH
  17. Jannesari, Zahra; Tatari, Mehdi: An adaptive strategy for solving convection dominated diffusion equation (2020)
  18. Karl Wette: SWIGLAL: Python and Octave interfaces to the LALSuite gravitational-wave data analysis libraries (2020) arXiv
  19. Kenneth L. Ho: FLAM: Fast Linear Algebra in MATLAB - Algorithms for Hierarchical Matrices (2020) not zbMATH
  20. Kraft, Daniel: Computing the Hausdorff distance of two sets from their distance functions (2020)

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