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 11784 articles , 8 standard articles )

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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Amin, Rohul; Shah, Kamal; Asif, Muhammad; Khan, Imran; Ullah, Faheem: An efficient algorithm for numerical solution of fractional integro-differential equations via Haar wavelet (2021)
  3. Axelsson, Owe; Liang, Zhao-Zheng; Kruzik, Jakub; Horak, David: Inner product free iterative solution and elimination methods for linear systems of a three-by-three block matrix form (2021)
  4. Iavernaro, F.; Mazzia, F.; Mukhametzhanov, M. S.; Sergeyev, Ya. D.: Computation of higher order Lie derivatives on the infinity computer (2021)
  5. Monti, A.; Ponci, F.; Riva, M.: Electrical machine theory through finite element analysis. (to appear) (2021)
  6. Oberbroeckling, Lisa A.: Programming mathematics using MATLAB (2021)
  7. Abdi, Ali; Conte, Dajana: Implementation of second derivative general linear methods (2020)
  8. Abdi, Ali; Hojjati, Gholamreza: Projection of second derivative methods for ordinary differential equations with invariants (2020)
  9. Abdoh, D. A.; Kodur, V. K. R.; Liew, K. M.: Smoothed particle hydrodynamics modeling of the thermal behavior of double skin facades in fires considering the effects of venetian blinds (2020)
  10. Abrarov, Sanjar M.; Quine, Brendan M.: A rational approximation of the sinc function based on sampling and the Fourier transforms (2020)
  11. Agrawal, P. N.; Acu, A. M.; Ruchi, R.: (q)-generalized Bernstein-Durrmeyer polynomials (2020)
  12. Alammari, K.; Sasi, A.; Ahmadi, M.; Ahmadi, A.; Saif, M.: Hybrid memristor-CMOS based FIR filter design (2020)
  13. Aline Duarte, Noslen Hernández: SeqROCTM: A Matlab toolbox for the analysis of Sequence of Random Objects driven by Context Tree Models (2020) arXiv
  14. Alnafisah, Yousef: The implementation of approximate coupling in two-dimensional SDEs with invertible diffusion terms (2020)
  15. Amiraslani, Amirhossein; Corless, Robert M.; Gunasingam, Madhusoodan: Differentiation matrices for univariate polynomials (2020)
  16. Andò, Alessia; Breda, Dimitri: Collocation techniques for structured populations modeled by delay equations (2020)
  17. Andrica, Dorin; Bagdasar, Ovidiu: Recurrent sequences. Key results, applications, and problems (to appear) (2020)
  18. Anfinsen, Henrik; Aamo, Ole Morten: Stabilization and tracking control of a time-variant linear hyperbolic PIDE using backstepping (2020)
  19. Angermann, Anne; Beuschel, Michael; Rau, Martin; Wohlfarth, Ulrich: MATLAB -- Simulink -- Stateflow. Foundations, toolboxes, examples (to appear) (2020)
  20. Arora, Geeta; Bhatia, Gurpreet Singh: A meshfree numerical technique based on radial basis function pseudospectral method for Fisher’s equation (2020)

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