Work Description

Title: Adaptive Cancellation of Magnetic Noise Data Set Open Access Deposited

h
Attribute Value
Methodology
  • The magnetic noise signals were generated using 4 magnetic coils and signal generators. The noise signals were recorded at 50 Hz by a PNI RM3100 magnetometer.
Description
  • This data contains 3 magnetometer signals of 4 noise sources. It was created to test a Underdetermined Blind Source Separation algorithm for magnetic signals.
Creator
Depositor
  • aphoff@umich.edu
Contact information
Discipline
Funding agency
  • National Aeronautics and Space Administration (NASA)
Keyword
Date coverage
  • 2021-10
Resource type
Last modified
  • 11/20/2022
Published
  • 09/13/2022
DOI
  • https://doi.org/10.7302/bz6v-6q52
License
To Cite this Work:
Hoffmann, A. (2022). Adaptive Cancellation of Magnetic Noise Data Set [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/bz6v-6q52

Relationships

This work is not a member of any user collections.

Files (Count: 4; Size: 508 KB)

These files contain magnetometer data recorded by three PNI RM3100 magnetometers.
Each file contains 100 seconds of triaxial data.
The magnetic signals were generated using four copper coils.

Each of the three files contains data in separate columns in the following format.
Bx [nT] | By [nT] | Bz [nT] | Time [s]

Download All Files (To download individual files, select them in the “Files” panel above)

Best for data sets < 3 GB. Downloads all files plus metadata into a zip file.



Best for data sets > 3 GB. Globus is the platform Deep Blue Data uses to make large data sets available.   More about Globus

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.