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找到约 10,000 项符合「Matrix」的源代码

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www.eeworm.com/read/492400/6422255

m mog_p.m

function p = mog_P(x,covtype,means,invcovs,priors) %MOG_P Compute the probability density of a Mixture of Gaussians % % P = MOG_P(X,COVTYPE,MEANS,INVCOVS,PRIORS) % % Calculate the probability de
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m dlpdda.m

function W = dlpdda(x,nu,usematlab) %DLPDDA Distance Linear Programming Data Description attracted by the Average distance % % W = DLPDDA(D,NU) % % This one-class classifier works directly on th
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m dd_aic.m

function e = dd_aic(w,x) %DD_AIC compute the Akaike Information Criterion for MoG % % E = DD_AIC(W,X) % % Compute the Akaike Information Criterion of the Mixture of % Gaussians. We assume we have
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cpp 矩阵乘方和.cpp

/*描述 给出一个n*n的矩阵和正整数k,请求出S=A+A^2+A^3+A^4+...+A^k的值.A^x表示x个A相乘的结果. 关于输入 输入包含一组数据. 第一行是三个正整数n k m, (n
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rd oscorespls.fit.rd

%% $Id: oscorespls.fit.Rd 132 2007-08-24 09:21:05Z bhm $ \encoding{latin1} \name{oscorespls.fit} \alias{oscorespls.fit} \title{Orthogonal scores PLSR} \description{Fits a PLSR model with the orthogona
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rd simpls.fit.rd

%% $Id: simpls.fit.Rd 132 2007-08-24 09:21:05Z bhm $ \encoding{latin1} \name{simpls.fit} \alias{simpls.fit} \title{Sijmen de Jong's SIMPLS} \description{Fits a PLSR model with the SIMPLS algorithm.} \
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rd svdpc.fit.rd

%% $Id: svdpc.fit.Rd 89 2006-09-20 15:41:09Z bhm $ \encoding{latin1} \name{svdpc.fit} \alias{svdpc.fit} \title{Principal Component Regression} \description{Fits a PCR model using the singular value de
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rd widekernelpls.fit.rd

%% $Id: widekernelpls.fit.Rd 145 2007-10-12 08:56:32Z bhm $ \encoding{latin1} \name{widekernelpls.fit} \alias{widekernelpls.fit} \title{Wide Kernel PLS (R鋘nar et al.)} \description{Fits a PLSR model w
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c cluster.c

/***************************************************************** * HMMER - Biological sequence analysis with profile HMMs * Copyright (C) 1992-2003 Washington University School of Medicine * All
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m ss_tbl31.m

Gold sequences for the table of problem 3.1 of Spread Spectrum Chapter Note that the sequences are the columns of the below matrix not the rows, so we have to take the transpose of the following m