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 170 articles , 1 standard article )

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  1. Bezanson, Jeff; Edelman, Alan; Karpinski, Stefan; Shah, Viral B.: Julia: a fresh approach to numerical computing (2017)
  2. Quarteroni, Alfio; Saleri, Fausto; Gervasio, Paola: Scientific computing. Exercises and solved problems with MATLAB and Octave. (to appear) (2017)
  3. Rackl, Michael; Hanley, Kevin J.; Günthner, Willibald A.: Verification of an automated work flow for discrete element material parameter calibration (2017)
  4. Rogers, Simon; Girolami, Mark: A first course in machine learning (2017)
  5. Russell, Stephen; Madden, Niall: An introduction to the analysis and implementation of sparse grid finite element methods (2017)
  6. Sauer, Tomas: Prony’s method in several variables (2017)
  7. Aşici, Emel; Karaçal, Funda: Incomparability with respect to the triangular order. (2016)
  8. Babolian, Esmail; Javadi, Shahnam; Moradi, Eslam: Error analysis of reproducing kernel Hilbert space method for solving functional integral equations (2016)
  9. Beyrami, Hossein; Lotfi, Taher; Mahdiani, Katayoun: A new efficient method with error analysis for solving the second kind Fredholm integral equation with Cauchy kernel (2016)
  10. Blanes, Sergio; Casas, Fernando: A concise introduction to geometric numerical integration (2016)
  11. Botchev, Mikhail A.: Krylov subspace exponential time domain solution of Maxwell’s equations in photonic crystal modeling (2016)
  12. Boulton, Lyonell: Spectral pollution and eigenvalue bounds (2016)
  13. Cuvelier, François; Japhet, Caroline; Scarella, Gilles: An efficient way to assemble finite element matrices in vector languages (2016)
  14. Davis, Jon H.: Methods of applied mathematics with a software overview (2016)
  15. Jensen, Kristian Ejlebjerg; Gorman, Gerard: Details of tetrahedral anisotropic mesh adaptation (2016)
  16. Kassiénou, Lamien; Longin, Some; Mamadou, Ouedraogo: Using the adaptive mesh finite volume method to solve three test problems (2016)
  17. König, Marcel; Radtke, Lars; Düster, Alexander: A flexible C++ framework for the partitioned solution of strongly coupled multifield problems (2016)
  18. Linge, Svein; Langtangen, Hans Petter: Programming for computations -- MATLAB/Octave. A gentle introduction to numerical simulations with MATLAB/Octave (2016)
  19. Linge, Svein; Langtangen, Hans Petter: Programming for computations -- Python. A gentle introduction to numerical simulations with Python (2016)
  20. Marco Caliari, Simone Zuccher: INFFTM: Fast evaluation of 3d Fourier series in MATLAB with an application to quantum vortex reconnections (2016) arXiv

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