代码搜索：Variance
找到约 2,271 项符合「Variance」的源代码
代码结果 2,271
www.eeworm.com/read/184196/9117840
m noisecg.m
function noise=noisecg(N,a1,a2)
%NOISECG Analytic complex gaussian noise.
% NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian
% noise of length N with mean 0.0 and variance 1.0.
%
% NOISE=
www.eeworm.com/read/183445/9158674
m rbf_kernel.m
function x = RBF_kernel(a,b, sigma2)
% Radial Basis Function (RBF) kernel function for implicit higher dimension mapping
%
% X = RBF_kernel(a,b,sig2)
%
% 'sig2' contains the SQUARED variance of the R
www.eeworm.com/read/374698/9388856
m rbf_kernel.m
function x = RBF_kernel(a,b, sigma2)
% Radial Basis Function (RBF) kernel function for implicit higher dimension mapping
%
% X = RBF_kernel(a,b,sig2)
%
% 'sig2' contains the SQUARED variance of the R
www.eeworm.com/read/372592/9501150
txt d13r10.txt
Private Sub Command1_Click()
'PROGRAM D13R10
'Driver for routine KSONE
NPTS = 1000
EPS = 0.1
Dim DATA(1000)
IDUM& = -5
Print
Print Tab(5); "Variance Ratio K-S
www.eeworm.com/read/371636/9544070
m noisecg.m
function noise=noisecg(N,a1,a2)
%NOISECG Analytic complex gaussian noise.
% NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian
% noise of length N with mean 0.0 and variance 1.0.
%
% NOISE=
www.eeworm.com/read/360895/10072670
m rbf_kernel.m
function x = RBF_kernel(a,b, sigma2)
% Radial Basis Function (RBF) kernel function for implicit higher dimension mapping
%
% X = RBF_kernel(a,b,sig2)
%
% 'sig2' contains the SQUARED variance of the R
www.eeworm.com/read/163246/10168855
m noisecg.m
function noise=noisecg(N,a1,a2)
%NOISECG Analytic complex gaussian noise.
% NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian
% noise of length N with mean 0.0 and variance 1.0.
%
% NOISE=
www.eeworm.com/read/279422/10439016
m noisecg.m
function noise=noisecg(N,a1,a2)
%NOISECG Analytic complex gaussian noise.
% NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian
% noise of length N with mean 0.0 and variance 1.0.
%
% NOISE=
www.eeworm.com/read/161171/10440975
m noisecg.m
function noise=noisecg(N,a1,a2)
%NOISECG Analytic complex gaussian noise.
% NOISE=NOISECG(N,A1,A2) computes an analytic complex gaussian
% noise of length N with mean 0.0 and variance 1.0.
%
% NOISE=
www.eeworm.com/read/278889/10490520
m rbf_kernel.m
function x = RBF_kernel(a,b, sigma2)
% Radial Basis Function (RBF) kernel function for implicit higher dimension mapping
%
% X = RBF_kernel(a,b,sig2)
%
% 'sig2' contains the SQUARED variance of the R