代码搜索：Multivariate Analysis

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www.eeworm.com/read/329075/12983747

cpp centerinit.cpp

/* Context : Fuzzy Clustering Algorithms Author : Frank Hoeppner, see also AUTHORS file Description : implementation of class module CenterInit History
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cpp removetiny.cpp

/* Context : Fuzzy Clustering Algorithms Author : Frank Hoeppner, see also AUTHORS file Description : implementation of class module RemoveTiny History
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cpp eucliddistance.cpp

/* Context : Fuzzy Clustering Algorithms Author : Frank Hoeppner, see also AUTHORS file Description : implementation of class module EuclidDistance Hist
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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
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dat coursecatalog.dat

1 Mathematical Analysis 7 2 English 3.5 3 Chinese 2 4 Linear Algebra 6
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m condense.m

function sy=condense(y,n) % Condense y by a factor of n, where n is a non-zero positive integer. % Produces a shorter, approximate version of vector y, with each group % of n adjacent points in y
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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
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htm partiv.htm

Intro to Algorithms: PART IV: Advanced Design and Analysis Techniques
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m lpcauto.m

function [ar,e]=lpcauto(s,p,t,w) %LPCAUTO performs autocorrelation LPC analysis [AR,E]=(S,P,T,W) % Inputs: % s(ns) is the input signal % p is the order (default: 12) % t(
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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)
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