The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 30, 2026

Filed:

Feb. 17, 2021
Applicant:

Passivelogic, Inc., Salt Lake City, UT (US);

Inventors:

Troy Aaron Harvey, Salt Lake City, UT (US);

Jeremy David Fillingim, Salt Lake City, UT (US);

Assignee:

PassiveLogic, Inc., Holladay, UT (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/084 (2023.01); B60H 1/00 (2006.01); F24F 11/64 (2018.01); F24F 11/65 (2018.01); F24F 120/10 (2018.01); F24F 120/20 (2018.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01); G05B 19/042 (2006.01); G06F 17/16 (2006.01); G06F 30/18 (2020.01); G06F 30/27 (2020.01); G06F 119/08 (2020.01); G06N 3/04 (2023.01); G06N 3/047 (2023.01); G06N 3/048 (2023.01); G06N 3/063 (2023.01); G06N 3/08 (2023.01); G06Q 10/067 (2023.01); G06Q 50/163 (2024.01); F24F 140/50 (2018.01); G06F 119/06 (2020.01);
U.S. Cl.
CPC ...
G06N 3/084 (2013.01); B60H 1/00285 (2013.01); F24F 11/64 (2018.01); F24F 11/65 (2018.01); G05B 13/027 (2013.01); G05B 13/04 (2013.01); G05B 19/042 (2013.01); G06F 17/16 (2013.01); G06F 30/18 (2020.01); G06F 30/27 (2020.01); G06N 3/04 (2013.01); G06N 3/047 (2023.01); G06N 3/048 (2023.01); G06N 3/063 (2013.01); G06N 3/08 (2013.01); G06Q 10/067 (2013.01); G06Q 50/163 (2013.01); F24F 2120/10 (2018.01); F24F 2120/20 (2018.01); F24F 2140/50 (2018.01); G05B 2219/2614 (2013.01); G06F 2119/06 (2020.01); G06F 2119/08 (2020.01);
Abstract

Heterogenous neural networks are disclosed that have activation functions that hold multi-variable equations. These variables can be passed from one neuron to another. The neurons may be laid out in a topologically similar fashion to a physical system that the heterogenous neural network is modeling. A neural network may have inputs of more than one type. Only a portion of the inputs (a subdomain) may be optimized In such an instance, the neural network may run forward, backpropagate to all inputs, and then perform optimization only on those inputs which will be optimized.


Find Patent Forward Citations

Harvey, Troy. (2026). Neural networks with subdomain training (U.S. Patent No. 12670399). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/12670399

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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