12,396 results

Implements Principal Component Analysis (PCA) and Independent Component Analysis (ICA)

This package contains functions that implement Principal Component Analysis (PCA) and Independent Component Analysis (ICA).PCA and ICA are implemented as functions in this package, and multiple

Pattern recognition lab, an image classification toolbox using Knn classifier and corss-validation.

EEG brain-computer interface system for providing real-time speech entrainment neurofeedback

Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data. Computational Intelligence and Neuroscience, 2011, 1–9. https://doi.org/10.1155/2011/156869Rydesäter. P. (2019). TCP/UDP/IP Toolbox

Toolbox for the simulation and detection of coevolution in proteins

uses stationary wavelets to enhance independent components analysis artifact removal

Tutorial GUI to demonstrate basic functionality of various controls on the GUI

starting point for a typical image or data file analysis application. This application uses GUIDE to do the user interface design, and has most of the basic controls such as buttons, listboxes, checkboxes

Learn Fourier analysis using live scripts and apps.

# Fourier Analysis[](https://www.mathworks.com/matlabcentral/fileexchange/106725-fourier-analysis) or

Flexible Statistics Data Analysis Toolbox

)](https://matlab.mathworks.com/open/github/v1?repo=UniprJRC/FSDAexamples&file=Label_Univariate_Outliers_in_Boxplot.mlx) |---### **Interactive Principal component analysis non robust/robust** | Name | Analysis Type | View :eyes: | Run ▶️

Loop-free code routine to find a maximal subset of linearly independent columns in a matrix

This submission is a very simple code routine that I have used for many years for finding a maximal subset of linearly independent columns of a matrix. It is based on an old conversation with Bruno

Heat conduction in a magnesium robotics component with finite element analysis (FEA).

This finite element thermal analysis (FEA) examines the heat tolerance for a robotics component. A single domain heat conduction analysis is performed on the nearest robotic component to the heat

ScreenCapture gets a screen-capture image of any Matlab GUI handle, or specified screen area rectangle

Principal Component Analysis (PCA) on images in MATLAB (GUI)

explanation;https://medium.com/@abhilash.singh/principal-component-analysis-pca-on-images-in-matlab-a-graphical-user-interface-gui-3d4999ddd0d0For a detail understanding of PCA, please refer my lecture on PCA;https://www.youtube.com/watch?v=ZLpQ6cbHxmYEnjoy!!!

This app gives you an initial estimate of the size of airplane components which can be further optimized.

This app gives you an initial estimate of the size of airplane components which can be further optimized.

The codes implement the Uncorrelated Multilinear Principal Component Analysis (UMPCA) algorithm.

Matlab source codes for Uncorrelated Multilinear Principal Component Analysis (UMPCA) %[Algorithm]%The matlab codes provided here implement the UMPCA algorithm presented in the paper

Toolbox for automated sorting of cellular calcium signals from optical imaging data.

This toolbox includes routines for using principal component analysis (PCA) and independent component analysis (ICA) to extract cellular signals from imaging data sets. A full description and

Additional app building components to efficiently develop advanced user interfaces in MATLAB

# Widgets Toolbox - App Designer and Advanced App Components[![View Widgets Toolbox - App Designer and Advanced App Components on File

PCA : reduce features used in face recognition

- This program uses Principal Component Analysis to reduce the number of features used in face recognition. - This program allows you to set K if you know the number of Principal components needed or

Principal Component Analysis for Face Recognition

This program recognizes a face from a database of human faces using PCA. The principal components are projected onto the eigenspace to find the eigenfaces and an unknown face is recognized from the

Many-featured, platform independent file and directory picker.

regular expression filtering and navigation of the file system is easy. The output is configurable (cell, struct or char arrays). It is written entirely in M and so is platform independent.

MATLAB code for dimensionality reduction, fault detection, and fault diagnosis using KPCA.

Kernel Principal Component Analysis (KPCA)MATLAB code for dimensionality reduction, fault detection, and fault diagnosis using KPCAVersion 2.2, 14-MAY-2021Email: iqiukp@outlook.comMain

A two-dimensional histogram of Power Spectral Densities.

PCSA is a frequency domain analysis technique that can be used to transform PSDs (as those in a spectrogram) to the form of a two-dimensional histogram with frequency-magnitude bins. PCSA can be used

[labels roots] = graph_connected_components(connection_matrix)

http://simulations.narod.ru/Breadth-first search used. [labels rts] = graph_connected_components(C)C - connection matrixlabels =[1 1 1 2 2 3 3 ...] lenght(labels)=L, label for each vertexlabels(i

Class based Correlation Plots and KLD values for I and Q components.

Generates scatter plots of correlation between inphase and quadrature phase components in POlSAR imagery and computes the Kullback Leiber Divergence between them.

Interactive courseware module that addresses the qualitative analysis of ordinary differential equations taught in mathematics courses.

# Qualitative Analysis of ODEs[![View on File

Variance components analysis for population genetics data.

These files are an adaptation of the ANOVA variance component estimators to be used in the analysis of genetic data, specifically Cockerham's 1969 Theta. Formulae were adapted from Sokal and Rohlf

A toolbox for the design of complex machine learning experiments

Interactive courseware module that introduces transfer function analysis taught in system dynamics and controls courses.

# Transfer Function Analysis of Dynamic Systems[![View on File

This code used to learn and explain the code of PCA to apply this code in many applications.

This is a demonstration of how one can use PCA to classify a 2D data set.

Toolbox for nonlinear analysis of multivariate time series with ordinal-patterns-based measures

The OPA (ordinal-patterns-analysis) toolbox is intended for nonlinear analysis of multivariate time series with becoming more and more popular ordinal-patterns-based measures [1-5] which are

It is an under-determined blind source separation method.

An improved sparse component analysis (SCA) is developped. The SCA method is just defined in a framework before, but there no existing complete algorithm. We explore a compelte and automatical

component is retained if the associated eigenvalue is bigger than the 95th of the distribution of ei

% Parallel Analysis (PA) to for determining the number of components to retain from PCA. component is retained if the associated eigenvalue is bigger than the 95th of the distribution of eigenvalues

The codes implement two algorithms: Multilinear Principal Component Analysis (MPCA) and MPCA+LDA.

Matlab source codes for Multilinear Principal Component Analysis (MPCA) %[Algorithms]%The matlab codes provided here implement two algorithms presented in the paper "MPCA_TNN08_rev2012.pdf" included

This is a collection of all files used in the course of the episode "Modeling Physical Components"

This is a collection of all files used in the MATLAB and Simulink Racing Lounge episodes "Modeling Physical Components Part 1 and 2" for further reference.Part

Live scripts, files, and slides for "Structural and Thermal Analysis with MATLAB" webinar

In this submission, you will find the slides that were shown on the webinar "Structural and Thermal Analysis with MATLAB" originally broadcasted on April 4, 2018. These slides described the Partial

Implementation of PCA base line models for structural damage detection.

These files provide visual configuration of the electric network and its components.

Running script electric_grid_visualization one can visualize power network configuration already defined in excel files with its components.One of the challenging issues in electric system analysis

This file is PCA for large feature.

Small size of observation and huge features happens a lot in shape/image and bioinformatics analysis. This file provides an alternative way of perform PCA analysis.More detail about PCA please check

Round numeric array values to IEC 60063 resistor/capacitor values (E-Series of preferred numbers).

ROUND63 rounds numeric values to electronic component values defined in IEC 60063 (preferred numbers for resistor, capacitor, and inductor values, previously IEC 63). By default the rounding bin

Lists all the maximal independent sets and the maximal cliques of an undirected graph

Maximal Independent Sets and Maximal Cliques are useful in many applications. The naive way of listing them can be very computationally intensive. This package contains two functions, BK_MaxIS and

Companion material for the book "Introduction to Audio Analysis, A MATLAB approach"

This is the MATLAB code of the book:"Introduction to Audio Analysis, A MATLAB^® Approach", Theodoros Giannakopoulos and Aggelos Pikrakis, 2014, Academic Press, 9780080993881.Book

Functionality extension of the linkaxes command

A custom class that eases the use of Java AWT and Swing components in MATLAB

A Matlab Toolbox for Cooperative Game Theory

The circuit analysis toolbox allows you to perform an AC analysis of a circuit.

with several examples * Independent voltage and current source components * Resistor, inductor, and capacitor components * Current dependent current source, voltage dependent current

Expectation-Maximization Principal Component Analysis

handle large matrices, and runs fast on gpuArray matrices.The algorithm is described in Bailey, Stephen. "Principal Component Analysis with Noisy and/or Missing Data." Publications of the Astronomical

Generate C code for single and multicore devices on bare metal, RTOS, and middleware services

This support package provides guidelines and tooling that facilitate development of component models that you intend to deploy as function source code for integration with a scheduler and services of

This program calculates 8 image indices: Bias,Correlation,DIV,Entropy,ERGAS,Q,RASE and RMSE.

, RASE and RMSE). The purpose of the program is to produce the results fast, easily and in a convenient way for the user (see Outputs). Initially, its purpose was to perform index analysis in hyperspectral

Collection and a development kit of Matlab mex functions for OpenCV library

A simple function for the analysis of two- and three- dimensional frame structures

The stiffness method is used for matrix analysis of structures. this program is useful for analysis of Planar trusses, Space trusses, Beams, Planar frames and Space frames. End release of members in

ROV control system design and simulation toolbox

included as well. Besides the nonlinear and linear analysis are also presented.User can refer to the readme text file for installation guides.

Simple, fast and ease of implementation. The filter feature selection methods include Relief-F, PCC, TV, and NCA.

Factor Analysis by the Principal Components Method.

covariance relationships among many variables in terms of a few underlying and unobservable random quantities called factors. It can be considered as an extension of Principal Components Analysis, but its

IA2RMS is an adaptive MCMC algorithm, for drawing samples from univariate target distributions.

pdf is adapted via interpolation procedures. After some iterations, the generated samples are virtually independent. For more information, see http://a2rms.sourceforge.net/ or, - L. Martino, J. Read, D

This Package implements 'Eigenface' PCA based face recognition technique.

http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdfhttp://www.creighton.edu/fileadmin/user/HSL/docs/ref/Searching_-_Recall_Precision.pdfORL Dataset Description and sourceIntroduced by Ferdinand Samaria et al. in Parameterisation of a stochastic model for human face identificationThe ORL Database of Faces contains 400 images from 40

Principal Components / Empirical Orthogonal Function Analysis

Contains functions involved in Empirical Orthogonal Function Analysis (EOF), also known as Principal Components Analysis (PCA) with Monte Carlo significance testing and varimax rotation.

A Battery Electric Vehicle (BEV) model in Simscape for longitudinal powertrain analysis

This is a MATLAB Project containing a Battery Electric Vehicle (BEV) model and its components such as motor, high voltage battery, and longitudinal vehicle. This project demonstrates Simscape

This function is written largely based on nipals function from R chemometrics package.

Management of data tables, similar to dataframe in R, with enhanced plotting facilities.

override to automatically annotate the resulting plots with table meta-data when appropriate.The toolbox also contains facilities for statistical analysis of data tables, such as principal component analysis

Release 10.0301 of a collection of functions for analysis/display of seismic and well-log data.

A set of about 170 functions (plus support functions called by them) for analysis and display of exploration-seismic data and well logs. These functions read and write seismic data in standard SEG-Y