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/493294/6400008
m gendatb.m
%GENDATB Generation of banana shaped classes
%
% A = GENDATB(N,S)
%
% INPUT
% N number of generated samples of vector with
% number of samples per class
% S variance
www.eeworm.com/read/493294/6400287
m subsc.m
%SUBSC Subspace Classifier
%
% W = SUBSC(A,N)
% W = SUBSC(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Desired model dimensionality or fraction of retained
% variance per
www.eeworm.com/read/484548/6579588
m addcountingnoise.m
function noiseMatrix=addCountingNoise(matrix, coefficient)
% adds random numbers normally distributed with variance coefficeint*mean(image)
% to an image matrix
noiseMatrix=randn(size(matrix));
www.eeworm.com/read/400577/11572697
m gendatb.m
%GENDATB Generation of banana shaped classes
%
% A = GENDATB(N,S)
%
% INPUT
% N number of generated samples of vector with
% number of samples per class
% S variance
www.eeworm.com/read/400577/11573014
m subsc.m
%SUBSC Subspace Classifier
%
% W = SUBSC(A,N)
% W = SUBSC(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Desired model dimensionality or fraction of retained
% variance per
www.eeworm.com/read/256796/11939646
m gendatb.m
%GENDATB Generation of banana shaped classes
%
% A = GENDATB(N,S)
%
% INPUT
% N number of generated samples of vector with
% number of samples per class
% S variance
www.eeworm.com/read/255755/12057400
m gendatb.m
%GENDATB Generation of banana shaped classes
%
% A = GENDATB(N,S)
%
% INPUT
% N number of generated samples of vector with
% number of samples per class
% S variance
www.eeworm.com/read/255755/12057946
m subsc.m
%SUBSC Subspace Classifier
%
% W = SUBSC(A,N)
% W = SUBSC(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Desired model dimensionality or fraction of retained
% variance per
www.eeworm.com/read/341146/12105055
m aggvar.m
function H = aggvar(sequence,isplot)
%
% 'aggvar' estimate the hurst parameter of a given sequence with aggregate
% variance method.
%
% Inputs:
% sequence: the input sequence for estima
www.eeworm.com/read/150905/12248516
m gendatb.m
%GENDATB Generation of banana shaped classes
%
% A = GENDATB(N,S)
%
% INPUT
% N number of generated samples of vector with
% number of samples per class
% S variance