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:
Aug. 11, 2020

Filed:

Sep. 19, 2018
Applicant:

Hughes Network Systems, Llc, Germantown, MD (US);

Inventors:

Amit Arora, Germantown, MD (US);

Archana Gharpuray, Germantown, MD (US);

John Kenyon, Germantown, MD (US);

Assignee:

Hughes Network Systems, LLC, Germantown, MD (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04B 17/00 (2015.01); H04W 24/02 (2009.01); H04W 24/08 (2009.01); G06N 5/04 (2006.01); G06K 9/62 (2006.01); G06N 20/00 (2019.01); G06F 9/54 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6269 (2013.01); G06F 9/542 (2013.01); G06N 20/00 (2019.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training and using machine learning clustering models to determine conditions a satellite communication system. In some implementations, feature vectors for a time period are obtained. Each feature vector includes feature values that represent properties of a satellite communication system at a respective time during the time period. Each feature vector is provided as input to a machine learning model that assigns the feature vector to a based on the properties of the satellite communication system represented by the feature vector. Each cluster corresponds to a respective potential operating condition of the satellite communication system. Data is generated that indicates a likelihood that each potential operating condition is the actual operating condition based on a quantity of the feature vectors that have been assigned to the cluster corresponding to the potential operating condition during the time period.


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