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Adj.1.Gaussian - of or relating to Karl Gauss or his mathematical theories of magnetics or electricity or astronomy or probability; "Gaussian distribution"
References in periodicals archive ?
LAHORE -- District and Sessions Judge Lahore Aabid Gaussian Qureshi on Wednesday visited Camp Jail and released 69 prisoners involved in petty offences.
The Gaussian mixture model (GMM) is introduced to predict the posterior trajectory for a mobile target by training its prior trajectory.
Fortunately, the recently developed bias correction methods based on theories such as the Bayesian inference [10, 11, 12, 11], the Gaussian process modeling [14, 15] and the Copula [16, 12, 18] provide effective approaches to solve and quantify the additional sources of uncertainties introduced by the surrogate models in the MDO.
The different types of noises are Gaussian noise, salt and pepper noise, shot noise, quantization noise, film grain, anisotropic noise.
Being a general fading distribution, Nakagami-m fading model includes (as its singularities) other fading models such are Rayleigh distribution (by setting parameter m value m = 1), and one-sided Gaussian distribution (m = 1/2) [2].
A generic algorithm for numerically accurate likelihood evaluates spatial models characterized by a high-dimensional latent Gaussian process and non-Gaussian response variables.
IC Solder Joint Inspection Based on the Gaussian Mixture Model"
While in most cases, noise has Gaussian distribution, in biomedical images, noise is usually a combination of Poisson and Gaussian noises.
Support for on-off keying (OOK), binary frequency shift keying (FSK), minimum shift keying (MSK), Gaussian minimum shift keying (GMSK), and Gaussian frequency shift keying (GFSK) modulation schemes.
Richard Gott and made use of the Gaussian curve (named for German mathematician Carl Friedrich Gauss 1777-1855).
The negentropy approximation is needed to compute the difference between the function of the extracted signal and the function of a Gaussian vector that has the same mean and variance as the extracted signal.
To do this, we use simple Gaussian and Laplacian decomposition and utilize histogram distributions and edge selection to determine the distinct values of the low and high frequency information, respectively.