Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as...
Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses
About this item
Full title
Author / Creator
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
Formats
Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
Subjects
More information
Scope and Contents
Contents
Extracting information from radiofrequency (RF) signals using artificial neural networks at low energy cost is a critical need for a wide range of applications from radars to health. These RF inputs are composed of multiples frequencies. Here we show that magnetic tunnel junctions can process analogue RF inputs with multiple frequencies in parallel...
Alternative Titles
Full title
Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2731609915
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2731609915
Other Identifiers
E-ISSN
2331-8422
