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:
Mar. 26, 2024

Filed:

Jul. 29, 2022
Applicant:

Tektronix, Inc., Beaverton, OR (US);

Inventors:

John J. Pickerd, Hillsboro, OR (US);

Kan Tan, Portland, OR (US);

Assignee:

Tektronix, Inc., Beaverton, OR (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 11/27 (2006.01); G06F 1/02 (2006.01); G06F 11/22 (2006.01);
U.S. Cl.
CPC ...
G06F 11/27 (2013.01); G06F 1/022 (2013.01); G06F 11/2273 (2013.01);
Abstract

A test and measurement system has a test and measurement instrument, a test automation platform, and one or more processors, the one or more processors configured to execute code that causes the one or more processors to receive a waveform created by operation of a device under test, generate one or more tensor arrays, apply machine learning to a first tensor array of the one or more tensor arrays to produce equalizer tap values, apply machine learning to a second tensor array of the one of the one or more tensor arrays to produce predicted tuning parameters for the device under test, use the equalizer tap values to produce a Transmitter and Dispersion Eye Closure Quaternary (TDECQ) value, and provide the TDECQ value and the predicted tuning parameters to the test automation platform. A method of testing devices under test includes receiving a waveform created by operation of a device under test, generating one or more tensor arrays, applying machine learning to a first tensor array of the one or more tensor arrays to produce equalizer tap values, applying machine learning to a second tensor array of the one or more tensor arrays to produce predicted tuning parameters for the device under test, using the equalizer tap values to produce a Transmitter Dispersion Eye Closure Quaternary (TDECQ) value, and providing the TDECQ value and the predicted tuning parameters to a test automation platform.


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