Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...

Selecting more sustainable solvents is a crucial component to mitigating the environmental impacts of chemical processes. Numerous tools have been developed to address this problem within the ...

Abstract: In this proposal we present a Matlab-only implementation of a simple, novel, and fully incremental Principal Component Pursuit (PCP) algorithm for Video Background Modeling. Our ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Previous research has proven the efficiency of PCA in ...

% H = PCA_EXAMPLE_GUI_2D returns the handle to a new PCA_EXAMPLE_GUI_2D or the handle to % the existing singleton*. % PCA_EXAMPLE_GUI_2D('CALLBACK',hObject,eventData,handles,...) calls the local % ...

Times Observer photo by Josh Cotton Dr. Lyle Dosser greets students at the end of the school day. Dosser, a Warren Area High School graduate, has been selected to lead Beaty-Warren Middle School as ...

ABSTRACT: Influenced by the development of international monetary system and the fi-nancial crisis, the promotion of CNY internationalization has gradually evolved into the dual needs of both domestic ...

This repository contains two examples accompanying the series of blog posts titled Unifying MATLAB and Simulink: A User Story on Guy on Simulink. The workflow illustrated in this example ...

Background: Multiparametric magnetic resonance imaging (mpMRI) plays an important role in the diagnosis of prostate cancer (PCa) in the current clinical setting. However, the performance of mpMRI ...

Abstract: In this paper, a practical comparison is performed between the use of the principal component analysis method (PCA) and the multidimensional scaling method (MDS) for image classification ...