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 10782 articles , 8 standard articles )

Showing results 1 to 20 of 10782.
Sorted by year (citations)

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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Bhaumik, Shovan; Date, Paresh: Nonlinear estimation. Methods and applications with deterministic sample points (2020)
  3. Biermé, Hermine; Lacaux, Céline: Fast and exact synthesis of some operator scaling Gaussian random fields (2020)
  4. Botchev, M. A.; Knizhnerman, L. A.: ART: adaptive residual-time restarting for Krylov subspace matrix exponential evaluations (2020)
  5. Chan, Joshua; Koop, Gary; Poirer, Dale J.; Tobias, Justin L.: Bayesian econometric methods (2020)
  6. Colapinto, Cinzia; Jayaraman, Raja; La Torre, Davide: Goal programming models for managerial strategic decision making (2020)
  7. Dimitrios Tsiotas; Avraam Charakopoulos: VisExpA: Visibility expansion algorithm in the topology of complex networks (2020) not zbMATH
  8. Diniz, Paulo S. R.: Adaptive filtering. Algorithms and practical implementation (to appear) (2020)
  9. Graham, Bryan; de Paula, Aureo: The econometric analysis of network data (to appear) (2020)
  10. Hermann, Martin: Numerical analysis. Volume 1. Numerical methods for algebra problems (to appear) (2020)
  11. Kumar, Sandeep; Pathak, Ashish; Khan, Debashis: Mathematical theory of subdivision. Finite element and wavelet methods (2020)
  12. Li, Jichun; Chen, Yi-Tung: Computational partial differential equations using MATLAB (to appear) (2020)
  13. Oprzędkiewicz, Krzysztof; Dziedzic, Klaudia: PSO identification for discrete fractional order model of heat transfer process (2020)
  14. Ratnajeevan, S.; Hoole, H.; Hoole, Yovahn Yesuraiyan R.: Finite elements-based optimization. Electromagnetic product design and nondestructive evaluation (2020)
  15. Roul, Pradip; Prasad Goura, V. M. K.: A new higher order compact finite difference method for generalised Black-Scholes partial differential equation: European call option (2020)
  16. Singh, Harendra (ed.); Kumar, Devendra (ed.); Baleanu, Dumitru (ed.): Methods of mathematical modelling. Fractional differential equations (2020)
  17. Sundararajan, D.: Introductory circuit theory (to appear) (2020)
  18. Sun, Defeng; Toh, Kim-Chuan; Yuan, Yancheng; Zhao, Xin-Yuan: SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0) (2020)
  19. Wanhammar, Lars; Saramäki, Tapio: Digital filters using Matlab (to appear) (2020)
  20. Watson, Daniel W.; Karageorghis, Andreas; Chen, C. S.: The radial basis function-differential quadrature method for elliptic problems in annular domains (2020)

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