Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single stretching vibration...
2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
2D NMR: Homonuclear Correlation Spectroscopy (COSY)01:06

2D NMR: Homonuclear Correlation Spectroscopy (COSY)

Homonuclear correlation spectroscopy, or COSY, is a 2-dimensional NMR technique that provides information about coupled protons. Typically, the geminal and vicinal coupling are observed. For example, consider the COSY spectrum of ethyl acetate, where its 1D proton NMR spectrum is plotted along the vertical and horizontal axes with their corresponding chemical shift scale. Three spots on the diagonal corresponding to the three peaks in the 1D proton spectrum are called diagonal peaks. The COSY...
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Landscape and progress of global peptide drugs in obstetrics and gynaecology.

Journal of peptide science : an official publication of the European Peptide Society·2022
Same author

The progress of peptide vaccine clinical trials in gynecologic oncology.

Human vaccines & immunotherapeutics·2022
Same author

Importance of excluded duplicates reporting in a systematic review.

World journal of pediatrics : WJP·2021
Same author

Systematic review of comparing single-incision versus conventional laparoscopic right hemicolectomy for right colon cancer.

World journal of surgical oncology·2019
Same author

[A late-type star spectra outlier data mining system].

Guang pu xue yu guang pu fen xi = Guang pu·2014
Same author

[Automatic classification method of star spectrum data based on classification pattern tree].

Guang pu xue yu guang pu fen xi = Guang pu·2014

Related Experiment Video

Updated: Jun 21, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

[Research on two-stage fuzzy clustering method for spectrum data based on PSO].

Jiang-hui Cai1, Ji-fu Zhang, Xu-jun Zhao

  • 1School of Computer, Taiyuan University of Science and Technology, Taiyuan 030024, China. cjhjj@sohu.com

Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|July 25, 2009
PubMed
Summary

A novel two-stage fuzzy clustering approach (TSPFCM) enhances high-dimensional data analysis. This method improves upon Fuzzy C-means Clustering by using a new algorithm and a Particle Swarm Optimization (PSO) mechanism for spectrum data mining.

More Related Videos

Polarization-Sensitive Two-Photon Microscopy for a Label-Free Amyloid Structural Characterization
05:54

Polarization-Sensitive Two-Photon Microscopy for a Label-Free Amyloid Structural Characterization

Published on: September 8, 2023

Related Experiment Videos

Last Updated: Jun 21, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Polarization-Sensitive Two-Photon Microscopy for a Label-Free Amyloid Structural Characterization
05:54

Polarization-Sensitive Two-Photon Microscopy for a Label-Free Amyloid Structural Characterization

Published on: September 8, 2023

Area of Science:

  • Computer Science
  • Data Mining
  • Machine Learning

Context:

  • High-dimensional data presents challenges for traditional clustering algorithms.
  • Fuzzy C-means Clustering (FCM) is sensitive to initial conditions and can be trapped in local optima.
  • Spectrum data analysis requires robust and efficient clustering techniques.

Purpose:

  • To propose a novel high-dimensional clustering algorithm.
  • To introduce a two-stage fuzzy clustering approach (TSPFCM) that integrates a new clustering method with Particle Swarm Optimization (PSO).
  • To address the limitations of FCM, specifically its sensitivity to initial conditions and tendency towards local optima.

Summary:

  • A novel two-stage fuzzy clustering approach (TSPFCM) is presented for high-dimensional data.
  • The first stage employs a new clustering method, while the second stage utilizes PSO to refine initial cluster centers from FCM.
  • This integration aims to overcome the locality and initial condition sensitivity issues inherent in FCM.

Impact:

  • Demonstrates the feasibility and value of TSPFCM for clustering spectrum data.
  • Offers an improved clustering method for complex, high-dimensional datasets.
  • Provides a more robust approach to data mining in fields utilizing spectrum analysis.