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.


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