Sostools

We are pleased to introduce SOSTOOLS, a free MATLAB toolbox for formulating and solving sums of squares (SOS) optimization programs. SOSTOOLS can be used to specify and solve sum of squares polynomial problems using a very simple, flexible, and intuitive high-level notation. Currently, the SOS programs are solved using SeDuMi or SDPT3, both well-known semidefinite programming solver, with SOSTOOLS handling internally all the necessary reformulations and data conversion.


References in zbMATH (referenced in 246 articles )

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  1. Ahmadi, Mohamadreza; Valmorbida, Giorgio; Gayme, Dennice; Papachristodoulou, Antonis: A framework for input-output analysis of wall-bounded shear flows (2019)
  2. Briat, Corentin: Co-design of aperiodic sampled-data min-jumping rules for linear impulsive, switched impulsive and sampled-data systems (2019)
  3. Crespo, Luis G.; Colbert, Brendon K.; Kenny, Sean P.; Giesy, Daniel P.: On the quantification of aleatory and epistemic uncertainty using sliced-normal distributions (2019)
  4. Dressler, Mareike; Iliman, Sadik; de Wolff, Timo: An approach to constrained polynomial optimization via nonnegative circuit polynomials and geometric programming (2019)
  5. Fu, Rong; Sun, Hongfei; Zeng, Jianping: Exponential stabilisation of nonlinear parameter-varying systems with applications to conversion flight control of a tilt rotor aircraft (2019)
  6. González, Temoatzin; Sala, Antonio; Bernal, Miguel: A generalised integral polynomial Lyapunov function for nonlinear systems (2019)
  7. Li, Yang; Zhang, Hongbin; Zhang, Liangliang: Equivalence of several stability conditions for switched linear systems with dwell time (2019)
  8. Menini, Laura; Possieri, Corrado; Tornambè, Antonio: A linear algebra method to decompose forms whose length is lower than the number of variables into weighted sum of squares (2019)
  9. Papp, Dávid; Yildiz, Sercan: Sum-of-squares optimization without semidefinite programming (2019)
  10. Paulin, Daniel; Jasra, Ajay; Crisan, Dan; Beskos, Alexandros: Optimization based methods for partially observed chaotic systems (2019)
  11. Villaverde, Alejandro F.: Observability and structural identifiability of nonlinear biological systems (2019)
  12. Aßmann, Denis; Liers, Frauke; Stingl, Michael; Vera, Juan C.: Deciding robust feasibility and infeasibility using a set containment approach: an application to stationary passive gas network operations (2018)
  13. Behrends, Sönke; Hübner, Ruth; Schöbel, Anita: Norm bounds and underestimators for unconstrained polynomial integer minimization (2018)
  14. Borgers, D. P.; Postoyan, R.; Anta, A.; Tabuada, P.; Nešić, D.; Heemels, W. P. M. H.: Periodic event-triggered control of nonlinear systems using overapproximation techniques (2018)
  15. Degue, Kwassi H.; Efimov, Denis; Richard, Jean-Pierre: Stabilization of linear impulsive systems under dwell-time constraints: interval observer-based framework (2018)
  16. Hafstein, Sigurdur; Gudmundsson, Skuli; Giesl, Peter; Scalas, Enrico: Lyapunov function computation for autonomous linear stochastic differential equations using sum-of-squares programming (2018)
  17. Henning Seidler, Timo de Wolff: An Experimental Comparison of SONC and SOS Certificates for Unconstrained Optimization (2018) arXiv
  18. Lee, Jae Hyoung; Lee, Gue Myung: On minimizing difference of a SOS-convex polynomial and a support function over a SOS-concave matrix polynomial constraint (2018)
  19. Lee, Jon; Skipper, Daphne; Speakman, Emily: Algorithmic and modeling insights via volumetric comparison of polyhedral relaxations (2018)
  20. Lu, Junjie; She, Zhikun; Ge, Shuzhi Sam; Jiang, Xin: Stability analysis of discrete-time switched systems via multi-step multiple Lyapunov-like functions (2018)

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