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 145 articles , 1 standard article )

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  1. Aşici, Emel; Karaçal, Funda: Incomparability with respect to the triangular order. (2016)
  2. Babolian, Esmail; Javadi, Shahnam; Moradi, Eslam: Error analysis of reproducing kernel Hilbert space method for solving functional integral equations (2016)
  3. 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)
  4. Blanes, Sergio; Casas, Fernando: A concise introduction to geometric numerical integration (2016)
  5. Botchev, Mikhail A.: Krylov subspace exponential time domain solution of Maxwell’s equations in photonic crystal modeling (2016)
  6. Boulton, Lyonell: Spectral pollution and eigenvalue bounds (2016)
  7. Davis, Jon: Methods of applied mathematics with a software overview (to appear) (2016)
  8. Linge, Svein; Langtangen, Hans Petter: Programming for computations -- MATLAB/Octave. A gentle introduction to numerical simulations with MATLAB/Octave (2016)
  9. McAndrew, Alasdair: A computational introduction to digital image processing (2016)
  10. Sameen, Sheema; Barbuti, Roberto; Milazzo, Paolo; Cerone, Antonio; Del Re, Marzia; Danesi, Romano: Mathematical modeling of drug resistance due to KRAS mutation in colorectal cancer (2016)
  11. Spillane, Nicole: An adaptive multipreconditioned conjugate gradient algorithm (2016)
  12. Sugiyama, Masashi: Introduction to statistical machine learning (2016)
  13. Chleboun, Jan: Book review of: J. Rogel-Salazar, Essential MATLAB and Octave. (2015)
  14. Grewal, Mohinder S.; Andrews, Angus P.: Kalman filtering. Theory and practice with MATLAB (2015)
  15. Hartikainen, Markus E.; Lovison, Alberto: PAINT-SICon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization (2015)
  16. Heister, Timo; Rebholz, Leo G.: Scientific computing. For scientists and engineers (2015)
  17. Hutchinson, Ian H.: A student’s guide to numerical methods (2015)
  18. Ketabchi, R.; Mokhtari, R.; Babolian, E.: Some error estimates for solving Volterra integral equations by using the reproducing kernel method (2015)
  19. Li, Gang; Chang, Liping; Li, Sheng: Signals and systems. Fundamentals (2015)
  20. Löwe, Harald: Book review of: F. Thuselt and F. P. Gennrich, Praktische Mathematik mit MATLAB, Scilab und Octave (2015)

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