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.