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    • Bayesian Separation of Non-Stationary Mixtures of Dependent Gaus

    Metadata Updated: April 10, 2025

    In this work, we propose a novel approach to perform Dependent Component Analysis (DCA). DCA can be thought as the separation of latent, dependent sources from their observed mixtures which is a more realistic model than Independent Component Analysis (ICA) where the sources are assumed to be independent. In general, the sources can be spatio-temporally dependent and the mixing system may be non-stationary. Here, we propose a DCA algorithm, that combines concepts of particle filters and Markov Chain Monte Carlo (MCMC) methods in order to separate non-stationary mixtures of spatially dependent Gaussian sources.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date April 10, 2025
    Data Update Frequency irregular

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date November 12, 2020
    Metadata Updated Date April 10, 2025
    Publisher Dashlink
    Maintainer
    Identifier DASHLINK_215
    Data First Published 2010-09-22
    Data Last Modified 2025-03-31
    Public Access Level public
    Data Update Frequency irregular
    Bureau Code 026:00
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 63c7c0c6-d1ec-436c-9224-ec43bfbb8d5c
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://c3.nasa.gov/dashlink/resources/215/
    Program Code 026:029
    Source Datajson Identifier True
    Source Hash 2f44b5d109caf1cb6f45287c539dffecde870810ae84a8693b880ffadd0ca951
    Source Schema Version 1.1

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