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Gaussian radial basis function

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  • Radial basis function network — A radial basis function network is an artificial neural network that uses radial basis functions as activation functions. They are used in function approximation, time series prediction, and control.Network architectureRadial basis function (RBF) …   Wikipedia

  • Radial basis function — A radial basis function (RBF) is a real valued function whose value depends only on the distance from the origin, so that phi(mathbf{x}) = phi(||mathbf{x}||); or alternatively on the distance from some other point c , called a center , so that… …   Wikipedia

  • Gaussian beam — In optics, a Gaussian beam is a beam of electromagnetic radiation whose transverse electric field and intensity (irradiance) distributions are well approximated by Gaussian functions. Many lasers emit beams that approximate a Gaussian profile, in …   Wikipedia

  • Activation function — In computational networks, the activation function of a node defines the output of that node given an input or set of inputs. A standard computer chip circuit can be seen as a digital network of activation functions that can be ON (1) or OFF (0) …   Wikipedia

  • Support vector machine — Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. Viewing input data as two sets of vectors in an n dimensional space, an SVM will construct a separating hyperplane in that… …   Wikipedia

  • Determining the number of clusters in a data set — Determining the number of clusters in a data set, a quantity often labeled k as in the k means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem. For a certain …   Wikipedia

  • List of numerical analysis topics — This is a list of numerical analysis topics, by Wikipedia page. Contents 1 General 2 Error 3 Elementary and special functions 4 Numerical linear algebra …   Wikipedia

  • Polyharmonic spline — In mathematics, polyharmonic splines are used for function approximation and data interpolation.They are very useful for interpolation of scattered datain many dimensions.Polyharmonic splines are a special case of radial basis functions andare… …   Wikipedia

  • Nonlinear dimensionality reduction — High dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lies on an embedded non linear manifold within… …   Wikipedia

  • Predictive analytics — encompasses a variety of techniques from statistics and data mining that analyze current and historical data to make predictions about future events. Such predictions rarely take the form of absolute statements, and are more likely to be… …   Wikipedia

  • Thin plate spline — This is a brief derivation for the closed form solutions for smoothing Thin Plate Spline . Details about these splines can be found in (Wahba, 1990).Thin plate splines (TPS) were introduced to geometric design by Duchon (Duchon, 1976). The name… …   Wikipedia

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