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 9607 articles , 8 standard articles )

Showing results 1 to 20 of 9607.
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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Abdi, A.; Jackiewicz, Z.: Towards a code for nonstiff differential systems based on general linear methods with inherent Runge-Kutta stability (2019)
  3. Al-Araji, Ahmed S.: An adaptive swing-up sliding mode controller design for a real inverted pendulum system based on culture-bees algorithm (2019)
  4. Albrecht, Gudrun; Caliò, Franca; Miglio, Edie: Geometrically constrained surface (re)construction (2019)
  5. Ali, M. Syed; Yogambigai, J.; Saravanan, S.; Elakkia, S.: Stochastic stability of neutral-type Markovian-jumping BAM neural networks with time varying delays (2019)
  6. Andreas Nüßing, Maria Carla Piastra, Sophie Schrader, Tuuli Miinalainen, Heinrich Brinck, Carsten H. Wolters, Christian Engwer: duneuro - A software toolbox for forward modeling in neuroscience (2019) arXiv
  7. Angelini, Elena: Waring decompositions and identifiability via Bertini and Macaulay2 software (2019)
  8. An, Qi; Jiang, Weihua: Spatiotemporal attractors generated by the Turing-Hopf bifurcation in a time-delayed reaction-diffusion system (2019)
  9. Arangala, Crista: Exploring linear algebra: labs and projects with MATLAB (to appear) (2019)
  10. Arbabi, Hassan; Mezić, Igor: Prandtl-Batchelor theorem for flows with quasiperiodic time dependence (2019)
  11. 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)
  12. Báez-López, José Miguel David; Báez Villegas, David Alfredo: MATLAB handbook with applications to mathematics, science, engineering, and finance (2019)
  13. Barbara De Palma, Marco Erba, Luca Mantovani, Nicola Mosco: A Python program for the implementation of the GAMMA-method for Monte Carlo simulations (2019) not zbMATH
  14. Beck, Amir; Guttmann-Beck, Nili: FOM -- a MATLAB toolbox of first-order methods for solving convex optimization problems (2019)
  15. Brezinski, Claude; Redivo-Zaglia, Michela: The genesis and early developments of Aitken’s process, Shanks’ transformation, the $\varepsilon$-algorithm, and related fixed point methods (2019)
  16. Chelikowsky, James R.: Introductory quantum mechanics with MATLAB. For atoms, molecules, clusters, and nanocrystals (2019)
  17. Damarla, Seshu Kumar; Kundu, Madhusree: Fractional order processes. Simulation, identification, and control (2019)
  18. Daniel McDuff, Ethan Blackford: iPhys: An Open Non-Contact Imaging-Based Physiological Measurement Toolbox (2019) arXiv
  19. Deb, Anish; Roychoudhury, Srimanti: Control system analysis and identification with MATLAB. Block pulse and related orthogonal functions (2019)
  20. De Marchi, S.; Martínez, A.; Perracchione, E.: Fast and stable rational RBF-based partition of unity interpolation (2019)

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