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Dykstra's algorithm is a method that computes a point in the intersection of convex sets, and is a variant of the alternating projection method (also called the projections onto convex sets method). In its simplest form, the method finds a point in the intersection of two convex sets by iteratively projecting onto each of the convex set; it ...
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.
The intersection point above is for the infinitely long lines defined by the points, rather than the line segments between the points, and can produce an intersection point not contained in either of the two line segments. In order to find the position of the intersection in respect to the line segments, we can define lines L 1 and L 2 in terms ...
Find the segments r and t that (prior to the removal of s) were respectively immediately above and below it in T (if they exist). If r and t cross, add that crossing point as a potential future event in the event queue. If p is the crossing point of two segments s and t (with s below t to the left of the crossing), swap the positions of s and t ...
The function is only an abstract representation of a computation which, in practice, may be relatively complex. Some methods result in a τ {\displaystyle \tau } which is a closed-form continuous function while others need to be decomposed into a series of computational steps involving, for example, SVD or finding the roots of a polynomial.
As stated above, the complexity of finding a convex hull as a function of the input size n is lower bounded by Ω(n log n). However, the complexity of some convex hull algorithms can be characterized in terms of both input size n and the output size h (the number of points in the hull). Such algorithms are called output-sensitive algorithms.
Multivariate interpolation — the function being interpolated depends on more than one variable Barnes interpolation — method for two-dimensional functions using Gaussians common in meteorology; Coons surface — combination of linear interpolation and bilinear interpolation; Lanczos resampling — based on convolution with a sinc function
intersection of two polygons: window test. If one wants to determine the intersection points of two polygons, one can check the intersection of any pair of line segments of the polygons (see above). For polygons with many segments this method is rather time-consuming. In practice one accelerates the intersection algorithm by using window tests ...