Noisy independent component analysis of autocorrelated components

Jakob Knollmüller and Torsten A. Enßlin
Phys. Rev. E 96, 042114 – Published 9 October 2017

Abstract

We present a method for the separation of superimposed, independent, autocorrelated components from noisy multichannel measurement. The presented method simultaneously reconstructs and separates the components, taking all channels into account, and thereby increases the effective signal-to-noise ratio considerably, allowing separations even in the high-noise regime. Characteristics of the measurement instruments can be included, allowing for application in complex measurement situations. Independent posterior samples can be provided, permitting error estimates on all desired quantities. Using the concept of information field theory, the algorithm is not restricted to any dimensionality of the underlying space or discretization scheme thereof.

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  • Received 5 May 2017
  • Revised 4 August 2017

DOI:https://doi.org/10.1103/PhysRevE.96.042114

©2017 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsGeneral PhysicsGravitation, Cosmology & AstrophysicsInterdisciplinary PhysicsPhysics of Living SystemsPhysics Education ResearchParticles & Fields

Authors & Affiliations

Jakob Knollmüller and Torsten A. Enßlin

  • Max-Planck-Institut für Astrophysik, Karl-Schwarzschildstr. 1, 85748 Garching, Germany and Ludwig-Maximilians-Universität München, Geschwister-Scholl-Platz 1, 80539 Munich, Germany

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Issue

Vol. 96, Iss. 4 — October 2017

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