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  2. Plotting algorithms for the Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Plotting_algorithms_for...

    Analogous to the exterior case, once b is found, we know that all points within the distance of b/4 from c are inside the Mandelbrot set. There are two practical problems with the interior distance estimate: first, we need to find z 0 {\displaystyle z_{0}} precisely, and second, we need to find p {\displaystyle p} precisely.

  3. Indicator function - Wikipedia

    en.wikipedia.org/wiki/Indicator_function

    In classical mathematics, characteristic functions of sets only take values 1 (members) or 0 (non-members). In fuzzy set theory, characteristic functions are generalized to take value in the real unit interval [0, 1], or more generally, in some algebra or structure (usually required to be at least a poset or lattice).

  4. Projections onto convex sets - Wikipedia

    en.wikipedia.org/wiki/Projections_onto_convex_sets

    In mathematics, projections onto convex sets (POCS), sometimes known as the alternating projection method, is a method to find a point in the intersection of two closed convex sets. It is a very simple algorithm and has been rediscovered many times. [1] The simplest case, when the sets are affine spaces, was analyzed by John von Neumann.

  5. Voronoi diagram - Wikipedia

    en.wikipedia.org/wiki/Voronoi_diagram

    Let be a metric space with distance function .Let be a set of indices and let () be a tuple (indexed collection) of nonempty subsets (the sites) in the space .The Voronoi cell, or Voronoi region, , associated with the site is the set of all points in whose distance to is not greater than their distance to the other sites , where is any index different from .

  6. Convex optimization - Wikipedia

    en.wikipedia.org/wiki/Convex_optimization

    The feasible set of the optimization problem consists of all points satisfying the inequality and the equality constraints. This set is convex because D {\displaystyle {\mathcal {D}}} is convex, the sublevel sets of convex functions are convex, affine sets are convex, and the intersection of convex sets is convex.

  7. Logistic map - Wikipedia

    en.wikipedia.org/wiki/Logistic_map

    The two intersection points are (, +) = (,) and (, +) = (,), and the positions of these intersection points are constant and do not depend on the value of r. An example of a spider web projection of a trajectory on the graph of the logistic map, and the locations of the fixed points x f 1 {\displaystyle x_{f1}} and x f 2 {\displaystyle x_{f2 ...

  8. Julia set - Wikipedia

    en.wikipedia.org/wiki/Julia_set

    is the smallest closed set containing at least three points which is completely invariant under f. ⁡ is the closure of the set of repelling periodic points. For all but at most two points , the Julia set is the set of limit points of the full backwards orbit (). (This suggests a simple algorithm for plotting Julia sets, see below.)

  9. Point plotting - Wikipedia

    en.wikipedia.org/wiki/Point_plotting

    Using point plotting, one associates an ordered pair of real numbers (x, y) with a point in the plane in a one-to-one manner. As a result, one obtains the 2-dimensional Cartesian coordinate system . To be able to plot points, one needs to first decide on a point in plane which will be called the origin , and a couple of perpendicular lines ...