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  2. Numerov's method - Wikipedia

    en.wikipedia.org/wiki/Numerov's_method

    Numerov's method (also called Cowell's method) is a numerical method to solve ordinary differential equations of second order in which the first-order term does not appear. It is a fourth-order linear multistep method. The method is implicit, but can be made explicit if the differential equation is linear.

  3. Second-order cone programming - Wikipedia

    en.wikipedia.org/wiki/Second-order_cone_programming

    The "second-order cone" in SOCP arises from the constraints, which are equivalent to requiring the affine function (+, +) to lie in the second-order cone in +. [ 1 ] SOCPs can be solved by interior point methods [ 2 ] and in general, can be solved more efficiently than semidefinite programming (SDP) problems. [ 3 ]

  4. Minimal realization - Wikipedia

    en.wikipedia.org/wiki/Minimal_realization

    [1] [2] The realization is called "minimal" because it describes the system with the minimum number of states. [2] The minimum number of state variables required to describe a system equals the order of the differential equation; [3] more state variables than the minimum can be defined. For example, a second order system can be defined by two ...

  5. Quadratically constrained quadratic program - Wikipedia

    en.wikipedia.org/wiki/Quadratically_constrained...

    Popular solver with an API for several programming languages. Free for academics. MOSEK: A solver for large scale optimization with API for several languages (C++, java, .net, Matlab and python) TOMLAB: Supports global optimization, integer programming, all types of least squares, linear, quadratic and unconstrained programming for MATLAB.

  6. Convex optimization - Wikipedia

    en.wikipedia.org/wiki/Convex_optimization

    A hierarchy of convex optimization problems. (LP: linear programming, QP: quadratic programming, SOCP second-order cone program, SDP: semidefinite programming, CP: conic optimization.) Linear programming problems are the simplest convex programs. In LP, the objective and constraint functions are all linear. Quadratic programming are the next ...

  7. MUSCL scheme - Wikipedia

    en.wikipedia.org/wiki/MUSCL_scheme

    An example of MUSCL type state parabolic-reconstruction. It is possible to extend the idea of linear-extrapolation to higher order reconstruction, and an example is shown in the diagram opposite. However, for this case the left and right states are estimated by interpolation of a second-order, upwind biased, difference equation.

  8. Newmark-beta method - Wikipedia

    en.wikipedia.org/wiki/Newmark-beta_method

    It is widely used in numerical evaluation of the dynamic response of structures and solids such as in finite element analysis to model dynamic systems. The method is named after Nathan M. Newmark , [ 1 ] former Professor of Civil Engineering at the University of Illinois at Urbana–Champaign , who developed it in 1959 for use in structural ...

  9. Nonlinear programming - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_programming

    SciPy (de facto standard for scientific Python) has scipy.optimize solver, which includes several nonlinear programming algorithms (zero-order, first order and second order ones). IPOPT (C++ implementation, with numerous interfaces including C, Fortran, Java, AMPL, R, Python, etc.) is an interior point method solver (zero-order, and optionally ...