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/460435/7251017
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/455115/7377660
m normalise.m
% NORMALISE - Normalises image values to 0-1, or to desired mean and variance
%
% Usage:
% n = normalise(im)
%
% Offsets and rescales image so that the minimum value is 0
% and the maximum
www.eeworm.com/read/444592/7611193
m ukfdemo.m
%
% Unscented Kalman Filter (UKF)
%
clear all;
clc;
echo off;
% INITIALISATION AND PARAMETERS:
% ==============================
sigma = 1e-5; % Variance of the Gaussia
www.eeworm.com/read/442927/7641785
m randn2.m
function z = randn2(n)
%RANDN2 2D Gaussian random samples with mean 0 and variance 1
% Usage: OUT=RANDN2(N)
% OUT is an N-by-2 matrix of points drawn from a 2D gaussian
% distribution with mean
www.eeworm.com/read/441245/7672666
m pcaklm.m
%PCAKLM Principal Component Analysis/Karhunen-Loeve Mapping
% (PCA or MCA of overall/mean covariance matrix)
%
% [W,FRAC] = PCAKLM(TYPE,A,N)
% [W,N] = PCAKLM(TYPE,A,FRAC)
%
% INPUT
% A
www.eeworm.com/read/441245/7673181
m var.m
%VAR Datafile overload
%
% [V,U] = VAR(A,W)
%
% Computes variance V and mean U in a single run for speed.
www.eeworm.com/read/441245/7673235
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/439811/7701428
m ip_07_10.m
% MATLAB script for Illustrative Problem 10, Chapter 7.
clear
echo on
K=10;N=2*K;T=100;variance=1;
noise=sqrt(variance)*randn(1,N);
a=rand(1,36);
a=sign(a-0.5);
b=reshape(a,9,4);
% Generate th
www.eeworm.com/read/397102/8067978
m pca.m
%PCA Principal Component Analysis
%
% [W,alf] = pca(A,n)
% [W,n] = pca(A,alf)
%
% A principal component analysis is performed on the joint
% covarianve matrix of the data in A. If A is a labeled da
www.eeworm.com/read/244937/12830799
m ip_07_10.m
% MATLAB script for Illustrative Problem 10, Chapter 7.
clear
echo on
K=10;N=2*K;T=100;variance=1;
noise=sqrt(variance)*randn(1,N);
a=rand(1,36);
a=sign(a-0.5);
b=reshape(a,9,4);
% Generate th