gaussian


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Related to gaussian: Gaussian blur

gaus·si·an

(gows'ē-ăn),
Relating to or described by Johann K F Gauss. See: gaussian curve.

gaus·si·an

(gows'ē-ăn)
Relating to or described by Johann K. F. Gauss.
References in periodicals archive ?
An energy-efficient collaborative algorithm is introduced in [21] based on the neural network aggregation model and Gaussian particle filtering (GPF) estimation.
y(x) can be regarded as the realization of Gaussian process in which the both the mean and covariance functions respectively satisfy the conditions that E[G(x)] = [h.
Hence have applied bilateral filtering on images that are corrupted by additive white Gaussian noise with different values of variances.
In this paper we will propose approximation to the Gaussian Q-function, obtained based on the properties of Mils ratio approximation [10] for Q-function, but taking the into account composite properties of minimization MSE (Mean-square error).
The ROF model is targeted to efficiently remove Gaussian noise only.
The odds of us being right are 25 percent on the near end and 25 percent in the far end of the Gaussian curve.
T]x, w is the separating vector, x is the observed signals, y is the extracted signal, p is a positive constant, and v is a Gaussian vector with the same mean and variance as y.
To fuse a visual image V and an IR image I, we first compute the Gaussian images [bar.
ANALYSIS OF GAUSSIAN MIXTURE MODEL There are a variety of methods to estimate model parameters [6].
Typical results of statistical describe the prediction efficiency of software failures are given in Table 1 for the Chromium browser and in Table 2 for a system of Chromium-OS (columns in these tables are indicated by the letter G correspond to the activation function Gaussian, and columns indicated by the letters IM--to the activation function Inverse Multiquadric).
The Gaussian copula became popular due, in part, to its link to the familiar multivariate normal distribution.
In this article, first we present a mini review of signal detection under Gaussian noise, and then introduce two methods toward detection of gravitational waves under non-Gaussian noises to prepare for the forthcoming KAGRA.