PCA by Devinder

this implements the PCA algorithm. User can choose/input the no.of features in the reduced Dataset. (pca, image processing, computer vision)

featureNormalize(X)

pca(X,n)

main.m

Nipals algorithm for Principle Component Analysis by Qiaonan Duan

This function is written largely based on nipals function from R chemometrics package. (nipals, principal component a..., pca)

nipals(X,a,it,tol )

Direct LDA and PCA+LDA by Vipin Vijayan

Implementation of LDA, Direct LDA and PCA+LDA. See description for details. (linear discriminant a..., lda, fischers linear discr...)

directlda(X,y,k,method,m)

directlda_demo

fld(X, L, n, crit, qrf, r, e, M )

Total Least Squares Method by Ivo Petras

Mathematical method known as total least squares or orthogonal regression or error-in-variables. (total least squares, svd, errorinvariables)

[Err, min_param]=numerFminD(fun, p, LBa, UBa, xdata, ydata,...

[Err, min_param]=numerFminS(fun, p, LBa, UBa, xdata, ydata)

[F, Srez, Scel]=statindexes(XData, YData, a, b)

thumbnailScatter.m puts thumbnails over datapoints for better visualization by Derya

Helps you visualize patterns in your data. (visualization, pca, gui)

thumbnailScatter(dataX,dataY,thumbnailPath)

demo_scatterThumbnail.m

Kernel PCA and Pre-Image Reconstruction by Quan Wang

standard PCA, Gaussian kernel PCA, polynomial kernel PCA, pre-image reconstruction (signal processing, large data, dimension reduction)

K=kernel(X,type,para)

Y=PCA(X,d)

[Y, eigVector, para]=kPCA(X,d,type,para)

SimpleScores by Giuseppe Elia

Plots the PCA scores using the princomp(X) function. Loads files direct from .csv. (data analysis, pca, scores)

SimpleScores(varargin)

principal_component_analysis_forAnImage by raviteja nellore

principal component analysis applied to an image (pca, principal component a...)

pca_img.m

Fischer Linear Dicriminant Analysis by Sergios Petridis

find the discriminative susbspace for samples using fischer linear dicriminant analysis (statistics, machine learning, pattern recognition)

fld(X, L, n, crit, qrf, r, e, M )

Multilinear Principal Component Analysis (MPCA) by Haiping Lu

The codes implement two algorithms: Multilinear Principal Component Analysis (MPCA) and MPCA+LDA. (image processing, video processing, dimensionality reduct...)

MPCA(TX,gndTX,testQ,maxK)

MPCALDA(TX,gndTX,MPCADADim,testQ,maxK)

[GaitDBDir,probes,numprobe]=testData

KL Transform (Karhunen–Loève Theorem) by debasish

a simple code that performs KL transform. (image processing, image transform, pca)

assignment5_klt.m

Corresponding Points through MDL by Dirk-Jan Kroon

Minimum Description Length optimization of PCA model for 2D/3D ASM model building (mdl, minimum description l..., pca)

A=imresize3d(V,scale,tsize,ntype,npad)

AffineGradient2D( UpdateAffine,mappingdata,options)

Alpha=UniformLine(nLandmarks)

American Sign Language Detection using PCA and LDA by Neeraj

Provides scripts for testing the two algorithms as well as testing real time input. (american sign languag..., pca, lda)

ASLfisher(ImgMat,V_PCA,nRows,nColumns,omega,Class_number,Cl...

ASLsvm(cAlpha,nTrainingSamples,InImWeight,omega)

ASlknn(cAlpha,nTrainingSamples,InImWeight,omega)

Uncorrelated Multilinear Principal Component Analysis (UMPCA) by Haiping Lu

The codes implement the Uncorrelated Multilinear Principal Component Analysis (UMPCA) algorithm. (dimensionality reduct..., feature extraction, image processing)

UMPCA(TX,numP)

maxeig(A)

The PhD face recognition toolbox by Vitomir Struc

Useful functions for face recognition research. (epc curve, kpca, kfa)

compute_kernel_matrix_PhD.m

construct_Gabor_filters_PhD.m

evaluate_results_PhD.m

Active Shape Model (ASM) and Active Appearance Model (AAM) by Dirk-Jan Kroon

Cootes 2D/3D Active Shape & Appearance Model for automatic image object segmentation and recognition (2d, active appearance mod..., active shape model)

A=imresize3d(V,scale,tsize,ntype,npad)

AAM_2D_example.m

AAM_3D_train_example.m

Nonlinear fuzzy robust pca by Pasi Luukka

Implementation of a nonlinear fuzzy robust pca. (pca, fuzzy, chemometrics)

[scores,loads]=nfrpca(x,LV,method)

Orthogonal Linear Regression in 3D-space by using Principal Components Analysis by Ivo Petras

Orthogonal Linear Regression by using PCA (fitting, pca, orthogonal regression)

fit_3D_data(XData, YData, ZData, geometry, visualization, s...

Feature Analysis by Iftekhar Tanveer

This program analyzes an arff file (weka) (feature selection, arff, lda)

LDA.m

FeatureAnalysis.m

PCA based image fusion by VPS Naidu

Image fusion is done using principal component analysis (pca, image fusion)

PCAimfuse_demo.m

CDF for Tracy-Widom (TW1) Distribution by Christopher Carr

Table of CDF for Beta=1 TW. (largest eigenvalue, pca, statistics)

PCA (Principal Component Analysis) by Alaa Tharwat

This code used to learn and explain the code of PCA to apply this code in many applications. (pca, good material)

PCA_Tutorial.m

Simulation of Forward Curve using PCA (principle component analysis) by Moeti Ncube

Method of simulation forward curves (prinicple component a..., forward curve, pca)

importfile(fileToRead1)

vecr(x)

simfwdcurve.m

GUI for Multivariate Image Analysis of 4-dimensional data by Kateryna Artyushkova

Multivariate Image Analysis of 4-dimensional image sequences using 2-step two-way and three-way ... (pca, simplisma, image analysis)

[Classes,Centres,FinalDistance]=dcKMeans(Data,k,InitCentres...

[M,mask]=profile_z(images);

[c,t]=trilin(c,ne,ishape)

EM PCA by Mo Chen

EM algorithm for principal component analysis (em, pca)

empca(X, p)

Principal Component Analysis by Mo Chen

Efficient PCA (dimensional reduction, pca)

pca(X, p)

modular pca by arindam

modular pca based face recognition on orl data base (image processing, pca, modular pca)

modularpca.m

Kernel PCA by Ambarish Jash

Non-linear dimension reduction using kernel PCA. (kernel pca, dimension reduction, pca)

kernelpca_tutorial(data_in,num_dim)

PCA based face recognition by Gholamreza (Shahab) Anbarjafari

This code is PCA base face recognition programme. (classification, face recognition, pca)

PCA_Face_Recognition.m

PCA (Principial Component Analysis) by Andreas

Principal Component Analysis Implementation of LindsaySmithPCA.pdf (pca, principal component a..., optimization)

pcafunc(struktur, dim)

Basic PCA based log-Likelihood Classifier by Dirk-Jan Kroon

PCA algorithm suitable for detection / recognition of 2D image "objects" (classification, recognition, likelihood)

[Lmean,Gmean,Cgppca,invCgppca,Vtot]=train_model(L,G)

[distanceL,distanceG,LogLikelihood]=apply_model(T,Lmean,Gme...

example_classifier_ms.m

CDF for Tracy-Widom Distribution of Gaussian Unitary Ensemble by Matthew Brenneman

Table of CDF for Beta=2 TW: approxs CDF of max eval from complex central white wishart matrix. (pca, largest eigenvalue, tracywidom)

Principal Component Analysis (PCA) in MATLAB by Siamak Faridani

This is a demonstration of how one can use PCA to classify a 2D data set. (classification, pca, principal component a...)

pca.m

Alaa Tharwat ToolBox by Alaa Tharwat

This toolBox used in the image processing(feature extraction and classification) (lda, svm, knn)

K=normalizekernel(x,kernel,kerneloption,xsup);

T=phispan(x,phitype,dilation,uo,a,bord1,bord2,Family,par);

T=waveletspan(x,dilation,uo,a,leftbound,rightbound);

Sign correction in SVD and PCA by Rasmus Bro

Determines the right sign of the singular vectors in SVD (score- and loading vectors in PCA) (evd, chemometrics, svd)

sign_flip(loads,X)

Principal components analysis (PCA) by Siqing Wu

Principal components analysis (PCA) (pca, principal components ..., probability)

pca(X, N, method)

Partial Least-Squares and Discriminant Analysis by Yi Cao

A tutorial and tool using PLS for discriminant analysis. (pca, pls, linear algebra)

Principal Component Analysis and Partial Least Squares

pls (X,Y,tol2)

PCAtool by Guillaume MAZE

Compute everything you need for EOF,EEOF,CEOF,SVD,lagged SVD (empirical orthogonal, compute, pcatool)

calCeof(M,N,METHOD)

calEeof(M,N,METHOD,NLAG,DT)

caleof(M,N,method);

FLD-based Face Recognition System by Amir Omidvarnia

This package implements 'Fisherface', a FLD-based face recognition system. (application, face recognition, fisher linear discrim...)

CreateDatabase(TrainDatabasePath)

FisherfaceCore(T)

Recognition(TestImage, m_database, V_PCA, V_Fisher, Project...

PCA-based Face Recognition System by Amir Omidvarnia

This package implements 'Eigenface', a PCA-based face recognition system. (eigenface, appearancebased metho..., pca)

CreateDatabase(TrainDatabasePath)

EigenfaceCore(T)

Recognition(TestImage, m, A, Eigenfaces)

Face Recognition by Ali Behboodian

Face recognition using eigenface system (application, principal component a..., pca)

out=load_database();

face_recognition.m

Multivariate analysis and preprocessing of spectral data by Kateryna Artyushkova

GUI for MVA of spectral data including various preprocessing options and three types of MVA analysis (multivariate, pca, statistics)

[BE,I]=vms_sp_read(filename,pl);

[BE,I]=vms_sp_read_casa(filename,pl);

[X_sh, sp_sh]=shift_spectra_diff(spectra, X);

Karhunen-Loeve Decomposition for Statistical Recognition and Detection by Alex Chirokov

Karhunen-Loeve Decomposition for Face Recognition (face, karhunen, image analysis)

out=ScaleImage(in)

KarhunenLoeve.m

GUI for Multivariate Image Analysis of Multispectral Images by Kateryna Artyushkova

A GUI for MIA of multispectral image data sets (PCA, Simplisma, MCR, classification). (image analysis, multivariate, pca)

Cont=Contingency(Mem1,Mem2)

DCAgg(Distance, Method, k)

LogFactorial(n)

NIPALS algorithm by MAHE Geoffrey

Principal components analysis. (analysis, nipals, pca)

[Tprinc,Lprinc,pc]=nipals2(tab,nbp)

Statistical Analysis Demo by Kas Sharma

Econometrics demo that loads 25 years of quarterly data, visualizes, uses principle components, ... (correlation, pca, statistics)

tvpmoney.m

Visualization Tools for Process Condition Monitoring by Rajiv Singh

MATLAB Graphics and solid visualization tools for statistical analysis. (statistics, probability, visualization)

choosepc(C,m,ind,x0)

compute_ellipsoid(M,C)

createPanner(f,varargin)