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

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 8024 articles , 8 standard articles )

Showing results 1 to 20 of 8024.
Sorted by year (citations)

1 2 3 ... 400 401 402 next

  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Abdallah, L.; Haddou, M.; Migot, T.: Solving absolute value equation using complementarity and smoothing functions (2018)
  3. Abdelmalek, Salem; Bendoukha, Samir: Global asymptotic stability for a SEI reaction-diffusion model of infectious diseases with immigration (2018)
  4. Abrarov, Sanjar M.; Quine, Brendan M.; Jagpal, Rajinder K.: A sampling-based approximation of the complex error function and its implementation without poles (2018)
  5. Ali, M.Syed; Yogambigai, J.; Kwon, O.M.: Finite-time robust passive control for a class of switched reaction-diffusion stochastic complex dynamical networks with coupling delays and impulsive control (2018)
  6. Almeida, Rui M.P.; Duque, José C.M.; Ferreira, Jorge; Robalo, Rui J.: Finite element schemes for a class of nonlocal parabolic systems with moving boundaries (2018)
  7. Apte, Shaila Dinkar: Random signal processing (2018)
  8. Berg, Dmitry B.; Simos, T.E.; Tsitouras, Ch.: Trigonometric fitted, eighth-order explicit numerov-type methods (2018)
  9. Berman, Paul R.: Introductory quantum mechanics. A traditional approach emphasizing connections with classical physics (2018)
  10. Bertaccini, Daniele; Durastante, Fabio: Iterative methods and preconditioning for large and sparse linear systems with applications (2018)
  11. Bestehorn, Michael: Computational physics. With worked out examples in FORTRAN and MATLAB (2018)
  12. Bornemann, Folkmar: Numerical linear algebra. A concise introduction with MATLAB and Julia (2018)
  13. Burkotová, Jana; Rachůnková, Irena; Staněk, Svatoslav; Weinmüller, Ewa B.; Wurm, Stefan: On nonlinear singular BVPs with nonsmooth data. I: Analytical results (2018)
  14. Bylina, Beata: The block WZ factorization (2018)
  15. Calvetti, Daniela; Dunlop, Matthew; Somersalo, Erkki; Stuart, Andrew: Iterative updating of model error for Bayesian inversion (2018)
  16. Casas, G.; Ferrer, A.; Oñate, E.: Approximating the Basset force by optimizing the method of van Hinsberg et al. (2018)
  17. Castelli, Roberto; Garrione, Maurizio: Some unexpected results on the Brillouin singular equation: fold bifurcation of periodic solutions (2018)
  18. Chen, Tianyi; Curtis, Frank E.; Robinson, Daniel P.: Farsa for $\ell_1$-regularized convex optimization: local convergence and numerical experience (2018)
  19. Chen, Xue-wen; Zhou, Yue: Modelling and analysis of automobile vibration system based on fuzzy theory under different road excitation information (2018)
  20. Constantinescu, Emil M.: Generalizing global error estimation for ordinary differential equations by using coupled time-stepping methods (2018)

1 2 3 ... 400 401 402 next