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/167879/9948760
m ssa.m
function [pc,s,v]=SSA(x,dim,tau)
%Syntax: [pc,s,v]=SSA(x,dim,tau)
%_______________________________
%
% Singular Spectrum Analysis for a time series.
%
% pc is the matrix with the principal compo
www.eeworm.com/read/362306/10006177
txt readmeraf2.txt
RAFISHER2CDA Canonical Discriminant Analysis. While RAFisher1 is a procedure
that produces very different functions for classification that are also called
linear discriminant analysis, RAFisher2cda
www.eeworm.com/read/355408/10267780
m uwb_monopulse1.m
% Title: UWB monopulse1
% Author: J C
% Summary: Plots the time and frequency waveforms for UWB analysis.
% MATLAB Release: R13
% Description: This m file plots the time and frequency
www.eeworm.com/read/161339/10423556
m uwb_monopulse1.m
% Title: UWB monopulse1
% Author: J C
% Summary: Plots the time and frequency waveforms for UWB analysis.
% MATLAB Release: R13
% Description: This m file plots the time and frequency
www.eeworm.com/read/160392/10536068
tex user_introduction.tex
\nonumchapter{Preface} \nonumsection{What are hybrid models}
Mathematical models reproduce the behavior of physical phenomena.
By considering the process at different levels of detail,
different model
www.eeworm.com/read/423552/10550029
readme
The model-free toolbox (mfBox)
-----------------------------------
Version 1.0 (10-Mar-2006)
http://research.fabian.theis.name
http://www-aglang.uni-regensburg.de
The model-free toolbox or mfBox for
www.eeworm.com/read/467759/7000771
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/374790/7097683
rpt paobiao.map.rpt
Analysis & Synthesis report for paobiao
Tue Oct 21 15:01:22 2008
Quartus II Version 7.0 Build 33 02/05/2007 SJ Full Version
---------------------
; Table of Contents ;
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www.eeworm.com/read/236873/7119105
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/299984/7139939
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