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 8200 articles , 8 standard articles )

Showing results 1 to 20 of 8200.
Sorted by year (citations)

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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Rashid, Adnan; Hasan, Osman: Formal analysis of continuous-time systems using Fourier transform (2019-2019)
  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. Sun, Jian-Qiao; Xiong, Fu-Rui; Schütze, Oliver; Hernández, Carlos: Cell mapping methods. Algorithmic approaches and applications (2019)
  5. Abdallah, L.; Haddou, M.; Migot, T.: Solving absolute value equation using complementarity and smoothing functions (2018)
  6. Abdelmalek, Salem; Bendoukha, Samir: Global asymptotic stability for a SEI reaction-diffusion model of infectious diseases with immigration (2018)
  7. Abdi, Ali; Hosseini, Seyyed Ahmad: The barycentric rational difference-quadrature scheme for systems of Volterra integro-differential equations (2018)
  8. Abrarov, Sanjar M.; Quine, Brendan M.; Jagpal, Rajinder K.: A sampling-based approximation of the complex error function and its implementation without poles (2018)
  9. 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)
  10. 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)
  11. Ansmann, Gerrit: Efficiently and easily integrating differential equations with JiTCODE, JiTCDDE, and JiTCSDE (2018)
  12. Anwar, M. Fazeel; Rehman, Mutti-Ur: Numerical computation of lower bounds of structured singular values (2018)
  13. Apte, Shaila Dinkar: Random signal processing (2018)
  14. Arens, Tilo; Hettlich, Frank; Karpfinger, Christian; Kockelkorn, Ulrich; Lichtenegger, Klaus; Stachel, Hellmuth: Mathematics (to appear) (2018)
  15. Belov, Alexey A.; Andrianova, Olga G.; Kurdyukov, Alexander P.: Control of discrete-time descriptor systems. An anisotropy-based approach (2018)
  16. Berg, Dmitry B.; Simos, T. E.; Tsitouras, Ch.: Trigonometric fitted, eighth-order explicit Numerov-type methods (2018)
  17. Berman, Paul R.: Introductory quantum mechanics. A traditional approach emphasizing connections with classical physics (2018)
  18. Bertaccini, Daniele; Durastante, Fabio: Iterative methods and preconditioning for large and sparse linear systems with applications (2018)
  19. Bestehorn, Michael: Computational physics. With worked out examples in FORTRAN and MATLAB (2018)
  20. Bhaya, Amit; Bliman, Pierre-Alexandre; Niedu, Guilherme; Pazos, Fernando A.: A cooperative conjugate gradient method for linear systems permitting efficient multi-thread implementation (2018)

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