non-Gaussian process
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Gaussian blur — Gaussian blur, named for Carl Friedrich Gauss, describes blurring an image by a Gaussian function. It is a widely used effect in graphics software, typically to reduce image noise and reduce detail. The visual effect of this blurring technique is … Wikipedia
Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… … Wikipedia
Gaussian network model — The Gaussian network model (GNM), one of many things named after Carl Gauss, is a representation of a biological macromolecule as an elastic mass and spring network to study, understand, and characterize mechanical aspects of its long scale… … Wikipedia
Gaussian elimination — In linear algebra, Gaussian elimination is an algorithm for solving systems of linear equations. It can also be used to find the rank of a matrix, to calculate the determinant of a matrix, and to calculate the inverse of an invertible square… … Wikipedia
Process gain — In a spread spectrum system, the process gain (or processing gain ) is the ratio of the spread (or RF) bandwidth to the unspread (or baseband) bandwidth. It is usually expressed in decibels (dB).For example, if a 1 kHz signal is spread to 100 kHz … Wikipedia
Point process — In statistics and probability theory, a point process is a type of random process for which any one realisation consists of a set of isolated points either in time or geographical space, or in even more general spaces. For example, the occurrence … Wikipedia
Large deviations of Gaussian random functions — A random function ndash; of either one variable (a random process), or two or more variables(a random field) ndash; is called Gaussian if every finite dimensional distribution is a multivariate normal distribution. Gaussian random fields on the… … Wikipedia
Contaminated Gaussian — noise is a non Gaussian noise, drawn from a Gaussian mixture process. This process has the following probability density function: Categories: Physics stubsNoise … Wikipedia
Gauss–Markov process — This article is not about the Gauss–Markov theorem of mathematical statistics. Gauss–Markov stochastic processes (named after Carl Friedrich Gauss and Andrey Markov) are stochastic processes that satisfy the requirements for both Gaussian… … Wikipedia
Dirichlet process — In probability theory, a Dirichlet process is a stochastic process that can be thought of as a probability distribution whose domain is itself a random distribution. That is, given a Dirichlet process , where H (the base distribution) is an… … Wikipedia
Determinantal point process — In mathematics, a determinantal point process is a stochastic point process, the probability distribution of which is characterized as a determinant of some function. Such processes arise as important tools in random matrix theory, combinatorics … Wikipedia
