Related Experiment Video
Updated: Aug 9, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Chemical rank estimation by noise perturbation in functional principal component analysist
Cheng-Jian Xu1, Yi-Zeng Liang, Yang Li
1College of Chemistry and Chemical Engineering, Institute of Chemometrics and Intelligent Analytical Instruments, Central South University, Changsha 410083, PR China.
Abstract:
Some kinds of chemical data are not only univariate or multivariate observations of classical statistics, but also functions observed continuously. Such special characters of the data, if being handled efficiently, will certainly improve the predictive accuracy. In this paper, a novel method, named noise perturbation in functional principal component analysis (NPFPCA), was proposed to determine the chemical rank of two-way data. In NPFPCA, after noise addition to the measured data, the smooth eigenvectors can be obtained by functional principal component analysis (FPCA). The eigenvectors representing noise are sensitive to the perturbation, on the other hand, those representing chemical components are not. Therefore, by comparing the difference of eigenvectors obtained by FPCA with noise perturbation and by traditional principal component analysis (PCA), the chemical rank of the system can be achieved accurately. Several simulated and real chemical data sets were analyzed to demonstrate the efficiency of the proposed method.
More Related Videos
09:01A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Published on: May 7, 2014
06:22Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
Published on: September 19, 2025
Related Concept Videos
¹H NMR: Interpreting Distorted and Overlapping Signals
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
Carbon-13 (¹³C) NMR: Overview
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)
¹H NMR Signal Integration: Overview
Expected Frequencies in Goodness-of-Fit Tests
Friedman Two-way Analysis of Variance by Ranks