MuPAD consists of a powerful symbolic engine, a language that is optimized for operating on symbolic math expressions, and an extensive set of mathematical functions and libraries. The MuPAD engine serves as the foundation of Symbolic Math Toolbox, whose notebook interface provides access to the complete MuPAD language. Computer algebra system (CAS).

This software is also referenced in ORMS.

References in zbMATH (referenced in 139 articles )

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  1. Vandecasteele, Hannes; Zieliński, Przemysław; Samaey, Giovanni: Efficiency of a micro-macro acceleration method for scale-separated stochastic differential equations (2020)
  2. Srajer, Filip; Kukelova, Zuzana; Fitzgibbon, Andrew: A benchmark of selected algorithmic differentiation tools on some problems in computer vision and machine learning (2018)
  3. Tunga, Burcu: A hybrid algorithm with cluster analysis in modelling high dimensional data (2018)
  4. Demiralp, Metin; Tuna, Süha: Zero interval limit perturbation expansion for the spectral entities of Hilbert-Schmidt operators combined with most dominant spectral component extraction: formulation and certain technicalities (2017)
  5. Wojas, Włodzimierz; Krupa, Jan: Familiarizing students with definition of Lebesgue integral: examples of calculation directly from its definition using Mathematica (2017)
  6. Klima, Richard E.; Sigmon, Neil P.; Stitzinger, Ernest L.: Applied abstract algebra with Maple and MATLAB (2016)
  7. Cox, David A.; Little, John; O’Shea, Donal: Ideals, varieties, and algorithms. An introduction to computational algebraic geometry and commutative algebra (2015)
  8. Karahoca, Adem; Tunga, M.: A polynomial based algorithm for detection of embolism (2015) ioport
  9. Tunga, Burcu; Demiralp, Metin: Weight optimization in HDMR with perturbation expansion method (2015)
  10. Tyszka, Apoloniusz: All functions (g:\mathbbN\to\mathbbN) which have a single-fold Diophantine representation are dominated by a limit-computable function (f:\mathbbN\backslash0\to\mathbbN) which is implemented in MuPAD and whose computability is an open problem (2015)
  11. Hunt, Brian R.; Lipsman, Ronald L.; Rosenberg, Jonathan M.: A guide to MATLAB. For beginners and experienced users. (2014)
  12. Khan-Afshar, Sanaz; Siddique, Umair; Mahmoud, Mohamed Yousri; Aravantinos, Vincent; Seddiki, Ons; Hasan, Osman; Tahar, Sofiène: Formal analysis of optical systems (2014)
  13. Lynch, Stephen: Dynamical systems with applications using MATLAB (2014)
  14. Robertz, Daniel: Formal algorithmic elimination for PDEs (2014)
  15. Demiralp, Metin; Tunga, Burcu: A probabilistic evolution approach trilogy. III: Temporal variation of state variable expectation values from Liouville equation perspective (2013)
  16. King, Simon A.: Minimal generating sets of non-modular invariant rings of finite groups (2013)
  17. Linton, S.; Hammond, K.; Konovalov, A.; Brown, C.; Trinder, P. W.; Loidl, H.-W.; Horn, P.; Roozemond, D.: Easy composition of symbolic computation software using SCSCP: a new Lingua Franca for symbolic computation (2013)
  18. Tunga, M. Alper; Demiralp, Metin: A novel method for multivariate data modelling: Piecewise Generalized EMPR (2013)
  19. Tunga, M. Alper; Demiralp, Metin: Bound analysis through HDMR for multivariate data modelling - CMMSE (2013)
  20. Tyszka, Apoloniusz; Molenda, Krzysztof; Sporysz, Maciej: An algorithm which transforms any Diophantine equation into an equivalent system of equations of the forms (x_i=1), (x_i+x_j=x_k), (x_i \cdotx_j=x_k) (2013)

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