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 Experiment Videos

An algorithm for separation of mixed sparse and Gaussian sources.

Ameya Akkalkotkar1, Kevin Scott Brown1,2,3,4

  • 1Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT, United States of America.

Plos One
|April 18, 2017
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Inflammation rewires the enteric nervous system through neurogenic monocyte recruitment.

The Journal of experimental medicine·2026
Same author

Clustering of chemical profiles of <i>Centella asiatica</i> cultivars, grown in greenhouses, allows grouping of metabolites with similar production trends.

Industrial crops and products·2025
Same author

Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host-microbiota and other multi-omic interactions.

Nature protocols·2024
Same author

Integrating High-Resolution Mass Spectral Data, Bioassays and Computational Models to Annotate Bioactives in Botanical Extracts: Case Study Analysis of <i>C. asiatica</i> Extract Associates Dicaffeoylquinic Acids with Protection against Amyloid-β Toxicity.

Molecules (Basel, Switzerland)·2024
Same author

Role of Sea Surface Physical Processes in Mixed-Layer Temperature Changes During Summer Marine Heat Waves in the Chile-Peru Current System.

Journal of geophysical research. Oceans·2022
Same author

Analysis of sloppiness in model simulations: Unveiling parameter uncertainty when mathematical models are fitted to data.

Science advances·2022

This study introduces Mixed ICA/PCA via Reproducibility Stability (MIPReSt), a new method for separating Gaussian and non-Gaussian sources in signal mixtures. MIPReSt effectively identifies and separates mixed sources, improving signal decomposition accuracy.

Area of Science:

  • Signal Processing
  • Statistical Analysis
  • Machine Learning

Background:

  • Independent Component Analysis (ICA) is widely used for signal decomposition.
  • ICA struggles with mixtures containing both Gaussian and non-Gaussian sources.
  • Existing methods lack effective separation of mixed Gaussian and non-Gaussian signals.

Purpose of the Study:

  • To develop a novel method for mixed Independent Component Analysis/Principal Component Analysis (ICA/PCA).
  • To accurately separate Gaussian and non-Gaussian sources in complex signal mixtures.
  • To determine the dimension of the non-Gaussian subspace within a mixture.

Main Methods:

  • Introduced Mixed ICA/PCA via Reproducibility Stability (MIPReSt).
  • Employed repeated estimations to rank source reproducibility.

Related Experiment Videos

  • Utilized subsampling and component stability assessment across varying data sizes.

    • Main Results:

    • MIPReSt successfully separates simulated and real-world (speech) signal mixtures.
    • The method accurately determines the non-Gaussian subspace dimension.
    • Demonstrated utility for mixtures of known and unknown composition.

    Conclusions:

    • MIPReSt offers a robust solution for mixed ICA/PCA problems.
    • The method enhances the accuracy of signal decomposition in complex scenarios.
    • MIPReSt provides a stable approach for identifying non-Gaussian components.