Matlab

MATLAB® is a high-level language and interactive environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java™. You can use MATLAB for a range of applications, including signal processing and communications, image and video processing, control systems, test and measurement, computational finance, and computational biology. More than a million engineers and scientists in industry and academia use MATLAB, the language of technical computing.

This software is also referenced in ORMS.

Keywords for this software

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References in zbMATH (referenced in 11158 articles , 8 standard articles )

Showing results 1 to 20 of 11158.
Sorted by year (citations)

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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Abdi, Ali; Hojjati, Gholamreza: Projection of second derivative methods for ordinary differential equations with invariants (2020)
  3. Amiraslani, Amirhossein; Corless, Robert M.; Gunasingam, Madhusoodan: Differentiation matrices for univariate polynomials (2020)
  4. Arora, Geeta; Bhatia, Gurpreet Singh: A meshfree numerical technique based on radial basis function pseudospectral method for Fisher’s equation (2020)
  5. Awawdeh, Fadi; Smail, Linda: Convergence analysis of a highly accurate Nyström scheme for Fredholm integral equations (2020)
  6. Balk, Bert M.; Barbero, Javier; Zofío, José L.: A toolbox for calculating and decomposing total factor productivity indices (2020)
  7. Barati, Ali; Atabaigi, Ali: Numerical simulations of two components ecological models with sinc collocation method (2020)
  8. Barros, E. G. D.; Van Den Hof, P. M. J.; Jansen, J. D.: Informed production optimization in hydrocarbon reservoirs (2020)
  9. Bashier, Eihab B. M.: Practical numerical and scientific computing with MATLAB and Python (to appear) (2020)
  10. Bauman, B.; Sommariva, A.; Vianello, M.: Compressed algebraic cubature over polygons with applications to optical design (2020)
  11. Berrut, Jean-Paul; Elefante, Giacomo: A periodic map for linear barycentric rational trigonometric interpolation (2020)
  12. Bhaumik, Shovan; Date, Paresh: Nonlinear estimation. Methods and applications with deterministic sample points (2020)
  13. Biermé, Hermine; Lacaux, Céline: Fast and exact synthesis of some operator scaling Gaussian random fields (2020)
  14. Botchev, M. A.; Knizhnerman, L. A.: ART: adaptive residual-time restarting for Krylov subspace matrix exponential evaluations (2020)
  15. Böttcher, Philipp C.; Otto, Andreas; Kettemann, Stefan; Agert, Carsten: Time delay effects in the control of synchronous electricity grids (2020)
  16. Bünger, Florian: A Taylor model toolbox for solving ODEs implemented in Matlab/INTLAB (2020)
  17. Buvoli, Tommaso: A class of exponential integrators based on spectral deferred correction (2020)
  18. Campagna, R.; Cuomo, S.; De Marchi, S.; Perracchione, E.; Severino, G.: A stable meshfree PDE solver for source-type flows in porous media (2020)
  19. Campos, Lucas Silveira; Loeffler, Carlos Friedrich; Netto, Fabrício Oliveira; dos Santos, Áquila de Jesus: Testing the accomplishment of the radial integration method with the direct interpolation boundary element technique for solving Helmholtz problems (2020)
  20. Cavoretto, R.; De Rossi, A.; Dell’Accio, F.; Di Tommaso, F.: An efficient trivariate algorithm for tetrahedral Shepard interpolation (2020)

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