本文的目的是探讨和分析util.random_noise函数中的Gaussian var参数的大小对生成随机噪声的影响。通过研究和理解Gaussian分布及其应用,我们将探讨如何选择合适的var值来达到我们期望的随机噪声效果。同时,我们也将探讨影响Gaussian var值大小的因素,以帮助读者更好地理解和应用Gaussian var参数。 通过深入分析util.random_noi...
This code will generate random noise or white noise with Gaussian method. Code for main.c is :#include <stdio.h> #include <stdlib.h> #include "frannor.h" int main(int argc, char **argv) { double *noise=NULL; int i; int ndata; unsigned int seed; if(argc!=2) { fprintf(stderr...
The cumulative distribution of the envelope of the sum of a sinusoidal signal, a number M of randomly phased interfering sine waves, and, possibly, Gaussian noise is expressed as the sum of Marcum's Q-function and an asymptotic series of Laguerre polynomials, much like the ordinary Edgeworth ...
It is shown that one of commonly used approximate methods is the description of non-Gaussian processes, signals and noise as a finite sequence of elements or cumulant functions. In this case, if a large number of terms of the sequence is used, an acceptable error of the description can be...
noise.jpg Add a test result Mar 7, 2016 noise.txt Add a test result Mar 7, 2016 View all files Repository files navigation README White-Gaussian-Noise-WGN This is the simple implement to get a random number of White Gaussian Noise. ...
[x,\tilde{x}]+\frac{g^2}{2}\tilde{x}^{\mathrm{T}}C_{\phi\phi}\tilde{x}\right) \end{equation}\\ Comparing (9) with the generating functional of a Gaussian noise with autocorrelation function C(t,s), we can directly write down the mean-field dynamics of a single representative...
where 𝜉𝑖(𝑡)ξi(t) represents a Gaussian white noise with zero mean and variance 〈𝜉𝑖(𝑡)𝜉𝑗(𝑡′)〉=2𝑇𝛿𝑖𝑗𝛿(𝑡−𝑡′)〈ξi(t)ξj(t′)〉=2Tδijδ(t−t′) and T is the temperature of a thermal bath. As in [17], here we are in...
The application of a Gaussian Markov Random Fields (GMRF) based Maximum A Posteriori Probability (MAP) estimation for image Gaussian noise filter was presented. According to the characteristics of the Gaussian noise, the restoration model of the degenerated image based on GMRF was built, and then ...
(Gaussian) kernel with diagonal bandwidth matrix46. The density was estimated over a grid of\(210 \times 210\)nodes and we computed the home range area (in m2) for various values: 100, 99, 95, 90, 80, ..., 20, 10% of the estimated density. Similarly to the distribution of ...
Data is generated by sampling each dimension of h from an independent Gaussian distribution and using the matrix Wh+μ to project this lower dimensional representation of the data into the observed, higher dimensional representation. Noise, specified by the diagonal covariance matrix D, is added ...