The MATLAB ODE suite. The paper presents mathematical and software developments that are the basis for a suite of programs for the solution of initial value problems y ’ =F(t,y), with initial conditions y(t 0 )=y 0 . The solvers for stiff problems allow the more general form M(t)y ’ =f(t,y) with a nonsingular and sparse matrix M(t). The programs are developed for MATLAB, which influences the choice of methods and their implementation

References in zbMATH (referenced in 221 articles , 1 standard article )

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  1. Schweizer, Wolfgang: Simulating physical systems. Computational physics with MATLAB (2017)
  2. Balajewicz, Maciej; Tezaur, Irina; Dowell, Earl: Minimal subspace rotation on the Stiefel manifold for stabilization and enhancement of projection-based reduced order models for the compressible Navier-Stokes equations (2016)
  3. Goulet, D.: Modeling, simulating, and parameter Fitting of biochemical kinetic experiments (2016)
  4. Kim, Philsu; Kim, Junghan; Jung, WonKyu; Bu, Sunyoung: An error embedded method based on generalized Chebyshev polynomials (2016)
  5. Kulikov, G.Yu.; Kulikova, M.V.: Estimating the state in stiff continuous-time stochastic systems within extended Kalman filtering (2016)
  6. Kulyamin, Dmitry V.; Dymnikov, Valentin P.: Numerical modelling of coupled neutral atmospheric general circulation and ionosphere D region (2016)
  7. Calvo, M.; Laburta, M.P.; Montijano, J.I.; Rández, L.: Runge-Kutta projection methods with low dispersion and dissipation errors (2015)
  8. Chalishajar, Dimplekumar; Chalishajar, Heena: Trajectory controllability of second order nonlinear integro-differential system: an analytical and a numerical estimation (2015)
  9. Gaudreau, P.; Hayami, K.; Aoki, Y.; Safouhi, H.; Konagaya, A.: Improvements to the cluster Newton method for underdetermined inverse problems (2015)
  10. Johnston, Stuart T.; Simpson, Matthew J.; Baker, Ruth E.: Modelling the movement of interacting cell populations: a moment dynamics approach (2015)
  11. Khuvis, Samuel; Gobbert, Matthias K.; Peercy, Bradford E.: Time-stepping techniques to enable the simulation of bursting behavior in a physiologically realistic computational islet (2015)
  12. Kuehn, Christian: Multiple time scale dynamics (2015)
  13. Kulikov, G.Yu.; Weiner, R.: A singly diagonally implicit two-step peer triple with global error control for stiff ordinary differential equations (2015)
  14. Laburta, M.P.; Montijano, J.I.; Rández, L.; Calvo, M.: Numerical methods for non conservative perturbations of conservative problems (2015)
  15. Nance, J.; Kelley, C.T.: A sparse interpolation algorithm for dynamical simulations in computational chemistry (2015)
  16. Rossides, Tasos; Lloyd, David J.B.; Zelik, Sergey: Computing interacting multi-fronts in one dimensional real Ginzburg Landau equations (2015)
  17. Tiago, Jorge: Numerical simulations for the stabilization and estimation problem of a semilinear partial differential equation (2015)
  18. Wei, Jiamin; Yu, Yongguang; Wang, Sha: Parameter estimation for noisy chaotic systems based on an improved particle swarm optimization algorithm (2015)
  19. Anguelov, R.; Dumont, Y.; Lubuma, J.M.-S.; Shillor, M.: Dynamically consistent nonstandard finite difference schemes for epidemiological models (2014)
  20. Bradley, Ben K.; Jones, Brandon A.; Beylkin, Gregory; Sandberg, Kristian; Axelrad, Penina: Bandlimited implicit Runge-Kutta integration for astrodynamics (2014)

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