代码搜索：Normalized
找到约 4,216 项符合「Normalized」的源代码
代码结果 4,216
www.eeworm.com/read/197918/7962112
m cg_fft.m
clear all;
figure(1);
clf;
set (gcf,'Name','CG - FFT, File: Nonname','NumberTitle','off')
set(gcf,'Units','normalized','Position',[0.2 0.4 0.6 0.48],'MenuBar','none');
figure(1);
U=1;
U_Old=U;
mbox=
www.eeworm.com/read/147682/5728066
m init_drnlms.m
% [w,x,d,y,e,p]=init_drnlms(L,w0,x0,d0)
%
% Creates and initializes the variables required for the
% Data Reusing Normalized Least Mean Squares algorithm.
%
% Input Parameters [Size]::
%
www.eeworm.com/read/147682/5728072
m init_nlms.m
% [w,x,d,y,e,p]=init_nlms(L,w0,x0,d0)
%
% Creates and initializes the variables required for the
% Normalized Least Mean Squares Adaptive Filter algorithm.
%
% Input Parameters [Size]::
www.eeworm.com/read/147682/5728101
m asptsovnlms.m
% [w,y,e,xb,p]= asptsovnlms(xn,xb,w,d,mu,L1,L2,p,b)
%
% Performs filtering and coefficient update using the
% Second Order Volterra Normalized Least Mean Squares
% Adaptive Filter algori
www.eeworm.com/read/147682/5728141
m init_leakynlms.m
% [w,x,d,y,e,p]=init_leakynlms(L,w0,x0,d0)
%
% Creates and initializes the variables required for the
% Leaky Normalized Least Mean Squares algorithm.
%
% Input Parameters::
% L : n
www.eeworm.com/read/493294/6400470
m dd_ex7.m
% Show how several one-class classifiers can be combined.
% To make the classifier outputs comparable, the outputs should be
% normalized using dd_normc
% Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org
www.eeworm.com/read/492400/6422304
m dd_ex7.m
% Show how several one-class classifiers can be combined.
% To make the classifier outputs comparable, the outputs should be
% normalized using dd_normc
% Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org
www.eeworm.com/read/400576/11573559
m dd_ex7.m
% Show how several one-class classifiers can be combined.
% To make the classifier outputs comparable, the outputs should be
% normalized using dd_normc
% Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org
www.eeworm.com/read/254734/12121610
m select.m
function New_Sample_Set=Select(Sample_Set,Sample_probability,loop,I,N)
%implement the Select part of tracking
New_image=I;
C_probability(1)=Sample_probability(1);
%calculate the normalized cum
www.eeworm.com/read/213240/15140046
m dd_ex7.m
% Show how several one-class classifiers can be combined.
% To make the classifier outputs comparable, the outputs should be
% normalized using dd_normc
% Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org