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 10027 articles , 8 standard articles )

Showing results 21 to 40 of 10027.
Sorted by year (citations)
  1. Arangala, Crista: Exploring linear algebra. Labs and projects with MATLAB (2019)
  2. Arbabi, Hassan; Mezić, Igor: Prandtl-Batchelor theorem for flows with quasiperiodic time dependence (2019)
  3. Averbuch, Amir Z.; Neittaanmäki, Pekka; Zheludev, Valery A.: Spline and spline wavelet methods with applications to signal and image processing. Volume III. Selected topics (2019)
  4. Baccouch, Mahboub; Kaddeche, Slim: Efficient Chebyshev pseudospectral methods for viscous Burgers’ equations in one and two space dimensions (2019)
  5. Báez-López, José Miguel David; Báez Villegas, David Alfredo: MATLAB handbook with applications to mathematics, science, engineering, and finance (2019)
  6. Baleanu, Dumitru; Alqurashi, Maysaa; Murugesan, Meganathan; Gnanaprakasam, Britto Antony Xavier: One dimensional fractional frequency Fourier transform by inverse difference operator (2019)
  7. Barbara De Palma, Marco Erba, Luca Mantovani, Nicola Mosco: A Python program for the implementation of the GAMMA-method for Monte Carlo simulations (2019) not zbMATH
  8. Baron, Michael: Probability and statistics for computer scientists (2019)
  9. Beck, Amir; Guttmann-Beck, Nili: FOM -- a MATLAB toolbox of first-order methods for solving convex optimization problems (2019)
  10. Becker, Sebastian; Jentzen, Arnulf: Strong convergence rates for nonlinearity-truncated Euler-type approximations of stochastic Ginzburg-Landau equations (2019)
  11. Beretta, Elena; Ratti, Luca; Verani, Marco: Detection of conductivity inclusions in a semilinear elliptic problem arising from cardiac electrophysiology (2019)
  12. Bian, Chentong; Zhu, Tong; Yin, Guodong; Xu, Liwei: Integrated speed planning and friction coefficient estimation algorithm for intelligent electric vehicles (2019)
  13. Borkar, Aseem V.; Borkar, Vivek S.; Sinha, Arpita: Aerial monitoring of slow moving convoys using elliptical orbits (2019)
  14. Brezinski, Claude; Redivo-Zaglia, Michela: Extrapolation methods for the numerical solution of nonlinear Fredholm integral equations (2019)
  15. Brezinski, Claude; Redivo-Zaglia, Michela: The genesis and early developments of Aitken’s process, Shanks’ transformation, the (\varepsilon)-algorithm, and related fixed point methods (2019)
  16. Brokate, Martin; Manchanda, Pammy; Siddiqi, Abul Hasan: Calculus for scientists and engineers (to appear) (2019)
  17. Buonomo, Bruno; Manfredi, Piero; d’Onofrio, Alberto: Optimal time-profiles of public health intervention to shape voluntary vaccination for childhood diseases (2019)
  18. Burd, Adrian: Mathematical methods in the Earth and environmental sciences (2019)
  19. Cafuta, Kristijan: Sums of Hermitian squares decomposition of non-commutative polynomials in non-symmetric variables using NCSOStools (2019)
  20. Cardenas-Cabrera, Jorge; Diaz-Charris, Luis; Torres-Carvajal, Andrés; Castro-Charris, Narciso; Romero-Fandiño, Elena; Ruiz Ariza, José David; Jiménez-Cabas, Javier: Model predictive control strategies performance evaluation over a pipeline transportation system (2019)