代码搜索：decomposition

找到约 1,689 项符合「decomposition」的源代码

代码结果 1,689
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m emd_online.m

function [imf,ort,nbit] = emd_online(x,t,stop,nbpresift,tst,tst2) %EMD_ONLINE (On Line Empirical Mode Decomposition) computes on-line EMD % % IMPORTANT: EMD_ONLINE does not truly apply EMD on-line b
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www.eeworm.com/read/268260/11146911

m ex031200.m

n = -5:10; x = sin(pi*n/2); k = -100:100; w = (pi/100)*k; % frequency between -pi and +pi X = x * (exp(-j*pi/100)).^(n'*k); % DTFT of x % signal decomposition [xe,xo,m] = evenodd(x,n);
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www.eeworm.com/read/333887/12656285

m emd_online.m

function [imf,ort,nbit] = emd_online(x,t,stop,nbpresift,tst,tst2) %EMD_ONLINE (On Line Empirical Mode Decomposition) computes on-line EMD % % IMPORTANT: EMD_ONLINE does not truly apply EMD on-line b
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www.eeworm.com/read/202129/15390401

m emd_online.m

function [imf,ort,nbit] = emd_online(x,t,stop,nbpresift,tst,tst2) %EMD_ONLINE (On Line Empirical Mode Decomposition) computes on-line EMD % % IMPORTANT: EMD_ONLINE does not truly apply EMD on-line b
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www.eeworm.com/read/200648/15428149

m morphbwt2.m

function X = morphbwt2(X, Level) %MORPHBWT2 2D morphological binary wavelet transform. % Y = MORPHBWT2(X,L) computes the L level decomposition of binary % image X using the 2D median morpholog
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www.eeworm.com/read/200618/15428543

m ghmap2.m

function b=ghmap2(a) %GHMAP2 Single-level discrete 2-D multi-wavelet transform. % GHM performs a single-level 2-D multiwavelet decomposition % using GHM multiwavelet with four multi-filters %
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www.eeworm.com/read/322305/7072516

m decompb.m

function [stochc,stochcf,VYEAR]=decompB(L,cal_beg_i,cal_end_i,for_end_i); %DECOMPB Moving average with rolling volatility daily data decomposition. % [STOCHC,STOCHCF]=DECOMPB(L,CAL_BEG_I,CAL_END_I,
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www.eeworm.com/read/439340/7712003

m naivebayes.m

%田宏宇《机器学习》作业2 function NaiveBayes() %Naive贝叶斯数据分类器 %clear all; % calc xmean,sigma and its eigen decomposition allsamples=[];%所有训练图像 load faceTemplet pattern; %faceTemplet人脸包结构说明： %pattern——1
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www.eeworm.com/read/159921/10588056

m oaosmo2.m

function [model] = oaosmo2( data, labels, ker, arg, C, tol, verb) % OAOSMO2 One-Agains-One multi-class decomposition solved by SMO L2. % [model] = oaosmo2( data, labels, ker, arg, C, tol, verb) % % In
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www.eeworm.com/read/159921/10588131

m~ oaosmo2.m~

function [model] = oaosmo2( data, labels, ker, arg, C, tol, verb) % OAOSMO2 One-Agains-One multi-class decomposition solved by SMO L2. % [model] = oaosmo2( data, labels, ker, arg, C, tol, verb) % % In
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