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  2. Art gallery problem - Wikipedia

    en.wikipedia.org/wiki/Art_gallery_problem

    In the geometric version of the problem, the layout of the art gallery is represented by a simple polygon and each guard is represented by a point in the polygon. A set S {\displaystyle S} of points is said to guard a polygon if, for every point p {\displaystyle p} in the polygon, there is some q ∈ S {\displaystyle q\in S} such that the line ...

  3. Shooting method - Wikipedia

    en.wikipedia.org/wiki/Shooting_method

    In numerical analysis, the shooting method is a method for solving a boundary value problem by reducing it to an initial value problem.It involves finding solutions to the initial value problem for different initial conditions until one finds the solution that also satisfies the boundary conditions of the boundary value problem.

  4. DIDO (software) - Wikipedia

    en.wikipedia.org/wiki/DIDO_(software)

    The MATLAB/DIDO toolbox does not require a "guess" to run the algorithm. This and other distinguishing features have made DIDO a popular tool to solve optimal control problems. [4] [7] [15] The MATLAB optimal control toolbox has been used to solve problems in aerospace, [11] robotics [1] and search theory. [2]

  5. Perspective-n-Point - Wikipedia

    en.wikipedia.org/wiki/Perspective-n-Point

    Perspective-n-Point [1] is the problem of estimating the pose of a calibrated camera given a set of n 3D points in the world and their corresponding 2D projections in the image. The camera pose consists of 6 degrees-of-freedom (DOF) which are made up of the rotation (roll, pitch, and yaw) and 3D translation of the camera with respect to the world.

  6. 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 ]

  7. Singularity function - Wikipedia

    en.wikipedia.org/wiki/Singularity_function

    The function () is the Heaviside step function: H(x) = 0 for x < 0 and H(x) = 1 for x > 0. The value of H(0) will depend upon the particular convention chosen for the Heaviside step function. Note that this will only be an issue for n = 0 since the functions contain a multiplicative factor of x − a for n > 0.

  8. Quadratically constrained quadratic program - Wikipedia

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

    There are two main relaxations of QCQP: using semidefinite programming (SDP), and using the reformulation-linearization technique (RLT). For some classes of QCQP problems (precisely, QCQPs with zero diagonal elements in the data matrices), second-order cone programming (SOCP) and linear programming (LP) relaxations providing the same objective value as the SDP relaxation are available.

  9. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    Solving an equation f(x) = g(x) is the same as finding the roots of the function h(x) = f(x) – g(x). Thus root-finding algorithms can be used to solve any equation of continuous functions. However, most root-finding algorithms do not guarantee that they will find all roots of a function, and if such an algorithm does not find any root, that ...