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 6402 articles , 8 standard articles )

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  1. Abdelmalek, Salem; Bendoukha, Samir: On the global asymptotic stability of solutions to a generalised Lengyel-Epstein system (2017)
  2. Alonso, Pedro; Ibáñez, Javier; Sastre, Jorge; Peinado, Jesús; Defez, Emilio: Efficient and accurate algorithms for computing matrix trigonometric functions (2017)
  3. Benzi, Michele; Simoncini, Valeria: Approximation of functions of large matrices with Kronecker structure (2017)
  4. Chuong, T.D.; Jeyakumar, V.: A generalized Farkas lemma with a numerical certificate and linear semi-infinite programs with SDP duals (2017)
  5. Diaz-Toca, Gema M.; Belhaj, Skander: Blind image deconvolution through Bezoutians (2017)
  6. Duffy, Dean G.: Advanced engineering mathematics with MATLAB (2017)
  7. Duriez, Thomas; Brunton, Steven L.; Noack, Bernd R.: Machine learning control -- taming nonlinear dynamics and turbulence (2017)
  8. Fawzi, Hamza; Saunderson, James: Lieb’s concavity theorem, matrix geometric means, and semidefinite optimization (2017)
  9. Gabbiani, Fabrizio; Cox, Steven: Mathematics for neuroscientists (to appear) (2017)
  10. Gao, Qing: Universal fuzzy controllers for non-affine nonlinear systems (2017)
  11. Gautschi, Walter: Monotonicity properties of the zeros of freud and sub-range freud polynomials: analytic and empirical results (2017)
  12. Grüne, Lars; Pannek, Jürgen: Nonlinear model predictive control. Theory and algorithms (2017)
  13. Herman, Russell L.: An introduction to Fourier analysis (2017)
  14. Lin, Hong; Su, Hongye; Shi, Peng; Shu, Zhan; Wu, Zheng-Guang: Estimation and control for networked systems with packet losses without acknowledgement (2017)
  15. Machado, L.; Monteiro, M.Teresa T.: A numerical optimization approach to generate smoothing spherical splines (2017)
  16. Monti, A.; Ponci, F.; Riva, M.: Electrical machine theory through finite element analysis. (to appear) (2017)
  17. Nicholls, David P.: Numerical solution of diffraction problems: a high-order perturbation of surfaces and asymptotic waveform evaluation method (2017)
  18. Pozrikidis, C.: Fluid dynamics. Theory, computation, and numerical simulation (2017)
  19. Rogers, Simon; Girolami, Mark: A first course in machine learning (2017)
  20. Schweizer, Wolfgang: Simulating physical systems. Computational physics with MATLAB (2017)

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