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 6239 articles , 8 standard articles )

Showing results 1 to 20 of 6239.
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  1. Alonso, Pedro; Ibáñez, Javier; Sastre, Jorge; Peinado, Jesús; Defez, Emilio: Efficient and accurate algorithms for computing matrix trigonometric functions (2017)
  2. Duffy, Dean G.: Advanced engineering mathematics with MATLAB (to appear) (2017)
  3. Duriez, Thomas; Brunton, Steven L.; Noack, Bernd R.: Machine learning control -- taming nonlinear dynamics and turbulence (2017)
  4. Herman, Russell L.: An introduction to Fourier analysis (2017)
  5. Lin, Hong; Su, Hongye; Shi, Peng; Shu, Zhan; Wu, Zheng-Guang: Estimation and control for networked systems with packet losses without acknowledgement (2017)
  6. Monti, A.; Ponci, F.; Riva, M.: Electrical machine theory through finite element analysis. (to appear) (2017)
  7. Rogers, Simon; Girolami, Mark: A first course in machine learning (2017)
  8. Shafai, Bahram: System identification and adaptive control (to appear) (2017)
  9. Sun, Jiguang; Zhou, Aihui: Finite element methods for eigenvalue problems (2017)
  10. Aavatsmark, Ivar: Interpretation of well-cell pressures on hexagonal grids in numerical reservoir simulation (2016)
  11. Adam, Lukáš; Branda, Martin: Nonlinear chance constrained problems: optimality conditions, regularization and solvers (2016)
  12. Alessio, Silvia Maria: Digital signal processing and spectral analysis for scientists. Concepts and applications (2016)
  13. Alfa, Attahiru S.: Applied discrete-time queues (2016)
  14. Al-Hdaibat, B.; Govaerts, W.; Kuznetsov, Yu.A.; Meijer, H.G.E.: Initialization of homoclinic solutions near Bogdanov-Takens points: Lindstedt-Poincaré compared with regular perturbation method (2016)
  15. Alombah, N.Henry; Fotsin, Hilaire; Ngouonkadi, E.B.Megam; Nguazon, Tekou: Dynamics, analysis and implementation of a multiscroll memristor-based chaotic circuit (2016)
  16. Alyoubi, A.; Ganesh, M.: Parallel mixed FEM simulation of a class of single-phase models with non-local operators (2016)
  17. Ansari, Moien Ahmad; Arora, Deepak; Ansari, Sana Parveen: Chaos control and synchronization of fractional order delay-varying computer virus propagation model (2016)
  18. Aşici, Emel; Karaçal, Funda: Incomparability with respect to the triangular order. (2016)
  19. Auchmuty, Giles: Book review of: A. Beck, Introduction to nonlinear optimization: theory, algorithms, and applications with MATLAB (2016)
  20. Averbuch, Amir Z.; Neittaanmäki, Pekka; Zheludev, Valery A.: Spline and spline wavelet methods with applications to signal and image processing. Volume II. Non-periodic splines (2016)

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