Symbolic Math Toolbox

Symbolic Math Toolbox provides functions for solving, plotting, and manipulating symbolic math equations. You can create, run, and share symbolic math code using the MATLAB® Live Editor. The toolbox provides libraries of functions in common mathematical areas such as calculus, linear algebra, algebraic and ordinary differential equations, equation simplification, and equation manipulation. Symbolic Math Toolbox lets you analytically perform differentiation, integration, simplification, transforms, and equation solving. Your computations can be performed either analytically or using variable-precision arithmetic, with the results displayed in mathematical typeset. You can share your symbolic work as live scripts with other MATLAB users or convert them to HTML or PDF for publication. You can generate MATLAB functions, Simulink® function blocks, and Simscape™ equations directly from symbolic expressions.


References in zbMATH (referenced in 34 articles )

Showing results 1 to 20 of 34.
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  1. Milan Batista: Elfun18 - A collection of MATLAB functions for the computation of elliptic integrals and Jacobian elliptic functions of real arguments (2019) not zbMATH
  2. Deng, Daiguo; Wu, Hefeng; Sun, Peng; Wang, Ruomei; Shi, Zhuo; Luo, Xiaonan: A new geometric modeling approach for woven fabric based on Frenet frame and spiral equation (2018)
  3. Fasi, Massimiliano; Higham, Nicholas J.: Multiprecision algorithms for computing the matrix logarithm (2018)
  4. Helfrich-Schkarbanenko, Andreas; Rapedius, Kevin; Rutka, Vita; Sommer, Aron: Automatically generated mathematical problems and solutions. Efficient teaching and learning with MATLAB (2018)
  5. Klein, Thierry; Fournier, Edouard; Grihon, Stéphane: A case study: influence of dimension reduction on regression trees-based algorithms -- predicting aeronautics loads of a derivative aircraft (2018)
  6. Shankar, P. Mohana: Differential equations. A problem solving approach based on MATLAB (2018)
  7. Srajer, Filip; Kukelova, Zuzana; Fitzgibbon, Andrew: A benchmark of selected algorithmic differentiation tools on some problems in computer vision and machine learning (2018)
  8. Esfandiari, Ramin S.: Numerical methods for engineers and scientists using MATLAB (2017)
  9. Higham, Desmond J; Higham, Nicholas J.: Matlab guide (2017)
  10. Mariarosaria Rizzardi: Algorithm 981: Talbot Suite DE: Application of Modified Talbot’s Method to Solve Differential Problems (2017) not zbMATH
  11. Tan, Guangning; Nedialkov, Nedialko S.; Pryce, John D.: Conversion methods for improving structural analysis of differential-algebraic equation systems (2017)
  12. Klima, Richard E.; Sigmon, Neil P.; Stitzinger, Ernest L.: Applied abstract algebra with Maple and MATLAB (2016)
  13. Skubov, D.; Lukin, A.; Popov, I.: Bifurcation curves for synchronous electrical machine (2016)
  14. Tan, Guangning; Nedialkov, Nedialko S.; Pryce, John D.: Symbolic-numeric methods for improving structural analysis of differential-algebraic equation systems (2016)
  15. Xue, Dingyü; Chen, YangQuan: Scientific computing with MATLAB (2016)
  16. Chleboun, Jan; Mikeš, Karel: Identification of parameters in initial value problems for ordinary differential equations. (2015)
  17. Kallinderis, Y.; Fotia, S.: A priori mesh quality metrics for three-dimensional hybrid grids (2015)
  18. Gong, Andong: Analytical integrations of the linearly interpolated triangular IBEM element with the aid of Matlab Symbolic Math Toolbox (2014)
  19. Hunt, Brian R.; Lipsman, Ronald L.; Rosenberg, Jonathan M.: A guide to MATLAB. For beginners and experienced users. (2014)
  20. Roque, C. M. C.: Symbolic and numerical analysis of plates in bending using Matlab (2014)

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