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US Patent 11228379 Radio signal processing network model search

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Is a
Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
112283790
Patent Inventor Names
Timothy James O'Shea0
Date of Patent
January 18, 2022
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Patent Application Number
160179520
Date Filed
June 25, 2018
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Patent Citations Received
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US Patent 11973540 Radio signal processing network model search
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US Patent 11700585 5G signals detection using neural network
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US Patent 11748414 Methods and systems of operating computerized neural networks for modelling CSR-customer relationships
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US Patent 11836220 Updating of statistical sets for decentralized distributed training of a machine learning model
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US Patent 11936343 Per-branch, combined, and grouped combined MIMO DPD
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US Patent 11599799 Digital signal processing with neural networks
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US Patent 11626932 Radio signal processing network model search
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US Patent 11636280 Updating of statistical sets for decentralized distributed training of a machine learning model
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Patent Primary Examiner
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Lana N Le
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Patent abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication. One of the methods includes: receiving an RF signal at a signal processing system for training a machine-learning network; providing the RF signal through the machine-learning network; producing an output from the machine-learning network; measuring a distance metric between the signal processing model output and a reference model output; determining modifications to the machine-learning network to reduce the distance metric between the output and the reference model output; and in response to reducing the distance metric to a value that is less than or equal to a threshold value, determining a score of the trained machine-learning network using one or more other RF signals and one or more other corresponding reference model outputs, the score indicating an a performance metric of the trained machine-learning network to perform the desired RF function.

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