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/393395/2474505
m computefrontier.m
function [E,V,MV_ExpectedValue,MV_Variance,SR_ExpectedValue,SR_Variance]=ComputeFrontier(Market,InvestorProfile)
% compute useful parameters
ExpectedValues=diag(Market.CurrentPrices)*(1+Market.Lin
www.eeworm.com/read/317063/13510951
cpp lgmm.cpp
#include "stdafx.h"
#include
#include
#include
#include
#include "lgmm.h"
#include "lgraph.h"
#include "DlgParameters.h"
#ifdef _DEBUG
#undef THIS_FIL
www.eeworm.com/read/421664/2049859
java~1~ variancecreatedemo.java~1~
package variance;
public class VarianceCreateDemo {
public static void main(String[] args) {
}
}
www.eeworm.com/read/398034/8008990
m sa_ex7_15b.m
sa% ESPRIT AOA estimation for a M = 4 element array with noise variance = .1
M = 4; % number of array elements
D = 2; % number of signals
sig2 = .1; % noise variance
th1 = -10*pi/180; %
www.eeworm.com/read/317326/13505863
m sa_ex7_15b.m
sa% ESPRIT AOA estimation for a M = 4 element array with noise variance = .1
M = 4; % number of array elements
D = 2; % number of signals
sig2 = .1; % noise variance
th1 = -10*pi/180; %
www.eeworm.com/read/365849/9843612
m var.m
function R = var(OBJ, N)
% VAR Variance of Gaussian noise
% VAR(W, T) returns variance of W at time T, T is ignored.
% VAR(W, T, N) same as above, N discarded for Gaussian noise.
% Copyright (C)
www.eeworm.com/read/325790/13184327
m var.m
function R = var(OBJ, N)
% VAR Variance of Gaussian noise
% VAR(W, T) returns variance of W at time T, T is ignored.
% VAR(W, T, N) same as above, N discarded for Gaussian noise.
% Copyright (C)
www.eeworm.com/read/325945/13173165
m estim_psi.m
% SCORE FUNCTION ESTIMATION BY THE GAUSSIAN KERNEL DENSITY ESTIMATOR
%-------------------------------------------------------------------------------
% sigma = variance of the Gaussian Kernel dens
www.eeworm.com/read/305247/13776072
m estim_psi.m
% SCORE FUNCTION ESTIMATION BY THE GAUSSIAN KERNEL DENSITY ESTIMATOR
%-------------------------------------------------------------------------------
% sigma = variance of the Gaussian Kernel dens
www.eeworm.com/read/209401/15220649
m estim_psi.m
% SCORE FUNCTION ESTIMATION BY THE GAUSSIAN KERNEL DENSITY ESTIMATOR
%-------------------------------------------------------------------------------
% sigma = variance of the Gaussian Kernel dens