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  2. Degeneracy (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Degeneracy_(graph_theory)

    In graph theory, a k-degenerate graph is an undirected graph in which every subgraph has at least one vertex of degree at most k: that is, some vertex in the subgraph touches k or fewer of the subgraph's edges. The degeneracy of a graph is the smallest value of k for which it is k-degenerate.

  3. Wiener–Khinchin theorem - Wikipedia

    en.wikipedia.org/wiki/Wiener–Khinchin_theorem

    For continuous time, the Wiener–Khinchin theorem says that if is a wide-sense-stationary random process whose autocorrelation function (sometimes called autocovariance) defined in terms of statistical expected value = [() ()] <,,, where the asterisk denotes complex conjugate, then there exists a monotone function in the frequency domain < <, or equivalently a non negative Radon measure on ...

  4. Incidence coloring - Wikipedia

    en.wikipedia.org/wiki/Incidence_coloring

    A graph is said to be k-generated if for every subgraph H of G, the minimum degree of H is at most k. Incidence chromatic number of k-degenerated graphs G is at most ∆(G) + 2k − 1. Incidence chromatic number of K 4 minor free graphs G is at most ∆(G) + 2 and it forms a tight bound. Incidence chromatic number of a planar graph G is at most ...

  5. Degeneracy (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Degeneracy_(mathematics)

    A degenerate conic is a conic section (a second-degree plane curve, defined by a polynomial equation of degree two) that fails to be an irreducible curve. A point is a degenerate circle, namely one with radius 0. [1] The line is a degenerate case of a parabola if the parabola resides on a tangent plane.

  6. Gauss–Markov process - Wikipedia

    en.wikipedia.org/wiki/Gauss–Markov_process

    A stationary Gauss–Markov process with variance (()) = and time constant has the following properties.. Exponential autocorrelation: () = | |.; A power spectral density (PSD) function that has the same shape as the Cauchy distribution: () = +. (Note that the Cauchy distribution and this spectrum differ by scale factors.)

  7. Wiener process - Wikipedia

    en.wikipedia.org/wiki/Wiener_process

    A single realization of a one-dimensional Wiener process A single realization of a three-dimensional Wiener process. In mathematics, the Wiener process (or Brownian motion, due to its historical connection with the physical process of the same name) is a real-valued continuous-time stochastic process discovered by Norbert Wiener.

  8. Weierstrass function - Wikipedia

    en.wikipedia.org/wiki/Weierstrass_function

    The computation of the Hausdorff dimension of the graph of the classical Weierstrass function was an open problem until 2018, while it was generally believed that = + ⁡ <. [6] [7] That D is strictly less than 2 follows from the conditions on and from above. Only after more than 30 years was this proved rigorously.

  9. Outerplanar graph - Wikipedia

    en.wikipedia.org/wiki/Outerplanar_graph

    There is a notion of degree of outerplanarity. A 1-outerplanar embedding of a graph is the same as an outerplanar embedding. For k > 1 a planar embedding is said to be k-outerplanar if removing the vertices on the outer face results in a (k − 1)-outerplanar embedding. A graph is k-outerplanar if it has a k-outerplanar embedding. [16]