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US Patent 11783196 Radio signal identification, identification system learning, and identifier deployment

Patent 11783196 was granted and assigned to Virginia Tech Intellectual Properties on October, 2023 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Virginia Tech Intellectual Properties
Virginia Tech Intellectual Properties
Current Assignee
Virginia Tech Intellectual Properties
Virginia Tech Intellectual Properties
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11783196
Patent Inventor Names
Timothy James O'Shea
Date of Patent
October 10, 2023
Patent Application Number
16864516
Date Filed
May 1, 2020
Patent Citations
‌
US Patent 10572830 Learning and deploying compression of radio signals
‌
US Patent 7502766 Neural networks decoder
‌
US Patent 8494464 Cognitive networked electronic warfare
‌
US Patent 10217047 Learning and deployment of adaptive wireless communications
‌
US Patent 10643153 Radio signal identification, identification system learning, and identifier deployment
Patent Citations Received
0
Patent Primary Examiner
‌
Eric Nilsson
CPC Code
‌
H04B 17/30
‌
H04W 24/08
‌
G06N 20/00
‌
G06N 3/0454
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G06N 3/08
Patent abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned identification of radio frequency (RF) signals. One of the methods includes: determining an RF signal configured to be transmitted through an RF band of a communication medium; determining first classification information that is associated with the RF signal, and that includes a representation of a characteristic of the RF signal or a characteristic of an environment in which the RF signal is communicated; using at least one machine-learning network to process the RF signal and generate second classification information as a prediction of the first classification information; calculating a measure of distance between (i) the second classification information that was generated by the at least one machine-learning network, and (ii) the first classification information associated with the RF signal; and updating the at least one machine-learning network based on the measure of distance.

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