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/237137/4631625
m turbo_icc.m
function [x_intf,x_sigma]=Turbo_ICC(x_rake,Rou,Mask,Noise_variance,x_mean0,x_variance0,SubslotData_length,Path_number)
% Gray coded 16-QAM mapping vector
MapMatrix16QAM = [-1-j -1-3*j -1+j -1+3*
www.eeworm.com/read/283135/9040833
m ds.m
function z=ds(nt)
% z=ds(nt):
% Function to analyze the degree of stationarity of data nt(n,m) by
% calculating the variance for each n, where n specifies the number
% of frequency
www.eeworm.com/read/373081/9475791
m ipcavarexp.m
function ipcavarexp(Model,No_of_PCs,labeltype)
% ipcavarexp makes a plot describing explained calibration variance for all intervals
%
% Input:
% Model (the output from iPCA.m)
% No_of_PCs:
www.eeworm.com/read/424116/10491086
m ipcavarexp.m
function ipcavarexp(Model,No_of_PCs,labeltype)
% ipcavarexp makes a plot describing explained calibration variance for all intervals
%
% Input:
% Model (the output from iPCA.m)
% No_of_PCs:
www.eeworm.com/read/278805/10507344
m p3_8.m
%%%%%%%-----Problem3.8-----%%%%%%%
%%Date 2007.4.17
%--------Settings--------%
clear all;
close all;
A=[-0.195 0.95;-1.5955 0.95;-1.9114 0.95];
segma_v2=1; %variance of noise
www.eeworm.com/read/349902/10786673
bff ava.bff
# BinaryFileFormat (leave this tag as magic token!)
# BVQX file format for *.AVA files (Analysis of VAriance file)
# AVA FileVersions supported: 2
#
# Version: v0.7a
# Build: 7072411
# Dat
www.eeworm.com/read/275215/10828427
m varianceratiotest.m
function [vrt,zvrt]=VRTest(x,q,cor)
%Syntax: [vrt,zvrt]=VRTest(x,q,cor)
%__________________________________
%
% Calculates the Variance Ratio Test (VRTest) of a time series x, with
% or without t
www.eeworm.com/read/417705/10979822
m fullpathcov.m
function [vars,rhobreaks,res]=FullPathCov(S)
% Given covariance matrix, compute full sparse PCA path
% Input:
% S: covariance matrix with decreasing diagonal
% Output:
% vars: vector of variance
www.eeworm.com/read/271244/11001989
m ds.m
function z=ds(nt)
% z=ds(nt):
% Function to analyze the degree of stationarity of data nt(n,m) by
% calculating the variance for each n, where n specifies the number
% of frequency
www.eeworm.com/read/454583/7387238
m portoptgads.m
%% Mean-variance portfolio optimization using GA and PATTERNSEARCH
%
% We seek to try out |ga| and |patternsearch| functions of the Genetic Algorithm and Direct Search Toolbox.
% We consider the un