Log in
Enquire now
‌

US Patent 10552738 Adaptive channel coding using machine-learned models

Patent 10552738 was granted and assigned to Google on February, 2020 by the United States Patent and Trademark Office.

OverviewStructured DataIssuesContributors

Contents

Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Applicant
Google
Google
Current Assignee
Google
Google
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10552738
Date of Patent
February 4, 2020
Patent Application Number
15380399
Date Filed
December 15, 2016
Patent Citations Received
‌
US Patent 12137350 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
3
‌
US Patent 12133083 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
4
‌
US Patent 12133084 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
5
‌
US Patent 12137349 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
6
‌
US Patent 10749594 Learning-based space communications systems
‌
US Patent 11563449 Systems for error reduction of encoded data using neural networks
‌
US Patent 10879620 Antenna directivity adjustment apparatus and antenna directivity adjustment method
‌
US Patent 11599773 Neural networks and systems for decoding encoded data
...
Patent Primary Examiner
‌
Austin Hicks
Patent abstract

The present disclosure provides systems and methods that enable adaptive training of a channel coding model including an encoder model, a channel model positioned structurally after the encoder model, and a decoder model positioned structurally after the channel model. The channel model can have been trained to emulate a communication channel, for example, by training the channel model on example data that has been transmitted via the communication channel. The channel coding model can be trained on a loss function that describes a difference between input data input into the encoder model and output data received from the decoder model. In particular, such a loss function can be backpropagated through the decoder model while modifying the decoder model, backpropagated through the channel model while the channel model is held constant, and then backpropagated through the encoder model while modifying the encoder model.

Timeline

No Timeline data yet.

Further Resources

Title
Author
Link
Type
Date
No Further Resources data yet.

References

Find more entities like US Patent 10552738 Adaptive channel coding using machine-learned models

Use the Golden Query Tool to find similar entities by any field in the Knowledge Graph, including industry, location, and more.
Open Query Tool
Access by API
Golden Query Tool
Golden logo

Company

  • Home
  • Press & Media
  • Blog
  • Careers
  • WE'RE HIRING

Products

  • Knowledge Graph
  • Query Tool
  • Data Requests
  • Knowledge Storage
  • API
  • Pricing
  • Enterprise
  • ChatGPT Plugin

Legal

  • Terms of Service
  • Enterprise Terms of Service
  • Privacy Policy

Help

  • Help center
  • API Documentation
  • Contact Us
By using this site, you agree to our Terms of Service.