Correlation‐based modeling and separation of geomagnetic field components | Zendy

Holschneider Matthias | Zendy; Lesur Vincent | Zendy; Mauerberger Stefan | Zendy; Baerenzung Julien | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

Correlation‐based modeling and separation of geomagnetic field components

Author(s) -

Holschneider Matthias,

Lesur Vincent,

Mauerberger Stefan,

Baerenzung Julien

Publication year - 2016

Publication title -

journal of geophysical research: solid earth

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.983

H-Index - 232

eISSN - 2169-9356

pISSN - 2169-9313

DOI - 10.1002/2015jb012629

Subject(s) - earth's magnetic field , computation , inversion (geology) , correlation , algorithm , computer science , bayesian probability , field (mathematics) , simple (philosophy) , a priori and a posteriori , approximate bayesian computation , separation (statistics) , geophysics , geology , magnetic field , mathematics , physics , artificial intelligence , machine learning , geometry , paleontology , philosophy , epistemology , quantum mechanics , structural basin , pure mathematics , inference

We introduce a technique for the modeling and separation of geomagnetic field components that is based on an analysis of their correlation structures alone. The inversion is based on a Bayesian formulation, which allows the computation of uncertainties. The technique allows the incorporation of complex measurement geometries like observatory data in a simple way. We show how our technique is linked to other well‐known inversion techniques. A case study based on observational data is given.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research