代码搜索：Multivariate Analysis
找到约 10,000 项符合「Multivariate Analysis」的源代码
代码结果 10,000
www.eeworm.com/read/462388/7201959
txt 3.txt
Q is a symmetric block cipher. It is defined for a block size of 128 bits. It allows arbitrary length passwords. The design is fairly conservative. It consists of a simple substitution-permutation net
www.eeworm.com/read/462388/7201962
txt 1.txt
Q is a symmetric block cipher. It is defined for a block size of 128 bits. It allows arbitrary length passwords. The design is fairly conservative. It consists of a simple substitution-permutation net
www.eeworm.com/read/462385/7202025
txt 3.txt
Q is a symmetric block cipher. It is defined for a block size of 128 bits. It allows arbitrary length passwords. The design is fairly conservative. It consists of a simple substitution-permutation net
www.eeworm.com/read/462385/7202030
txt 1.txt
Q is a symmetric block cipher. It is defined for a block size of 128 bits. It allows arbitrary length passwords. The design is fairly conservative. It consists of a simple substitution-permutation net
www.eeworm.com/read/460858/7239218
rpt ad.map.rpt
Analysis & Synthesis report for ad
Tue Apr 21 15:31:24 2009
Version 6.0 Build 178 04/27/2006 SJ Full Version
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; Table of Contents ;
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1. Legal Noti
www.eeworm.com/read/460435/7250414
m pca.m
%PCA Principal component analysis (PCA or MCA on overall covariance matrix)
%
% [W,FRAC] = PCA(A,N)
% [W,N] = PCA(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Number of dimensions
www.eeworm.com/read/458010/7314248
m lpcauto.m
function [ar,e,k]=lpcauto(s,p,t)
%LPCAUTO performs autocorrelation LPC analysis [AR,E,K]=(S,P,T)
% Inputs:
% s(ns) is the input signal
% p is the order (default: 12)
% t(nf,3)
www.eeworm.com/read/457011/7335300
rpt div.map.rpt
Analysis & Synthesis report for div
Sat Aug 25 16:02:47 2007
Version 6.0 Build 178 04/27/2006 SJ Full Version
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; Table of Contents ;
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1. Legal Not
www.eeworm.com/read/457011/7335325
rpt div.map.rpt
Analysis & Synthesis report for div
Sat Aug 25 16:02:47 2007
Version 6.0 Build 178 04/27/2006 SJ Full Version
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; Table of Contents ;
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1. Legal Not
www.eeworm.com/read/450608/7480077
m pca.m
%PCA Principal component analysis (PCA or MCA on overall covariance matrix)
%
% [W,FRAC] = PCA(A,N)
% [W,N] = PCA(A,FRAC)
%
% INPUT
% A Dataset
% N or FRAC Number of dimensions