公开(公告)号：US20240274222A1

公开(公告)日：2024-08-15

申请号：US18534495

申请日：2023-12-08

Applicant: Tektronix, Inc.

Inventor： Swapnil Jhawar ,  Chandra Sekhar Kappagantu ,  Mahesha Guttahalli Lakshmipathy ,  Sriram Mandyam Krishnakumar

IPC: G11C29/56

CPC classification number: G11C29/56004 ,  G11C29/56008 ,  G11C29/56016

Abstract: A test and measurement system includes a multi-stack test subsystem including a plurality of test and measurement instruments, each instrument coupled to a device under test (DUT) to receive a plurality of test signals from the DUT during a test mode of operation. One test and measurement instrument is designated as a master and the remainder are designated as extension test and measurement instruments. The master communicates control signals to each of the extensions to synchronize the test and measurement instruments to simultaneously acquire the plurality of test signals provided by the DUT. An automation engine is coupled to the multi-stack test subsystem to receive the acquired plurality of test signals from the master, and the automation engine analyzes the acquired test signals to perform validation testing for each of plurality of test signals and simultaneously display results of the validation testing for the plurality of test signals.

公开(公告)号：US20220036238A1

公开(公告)日：2022-02-03

申请号：US17386400

申请日：2021-07-27

Applicant: Tektronix, Inc.

Inventor： Karthikeyan R ,  Siby Charley P ,  John J. Pickerd ,  Saifee Jasdanwala ,  Chandra Sekhar Kappagantu ,  Mahesh Nair M

IPC: G06N20/00

Abstract: A system an input to receive a waveform signal, and one or more processors configured to execute code to cause the one or more processors to extract data bursts from the waveform signal, generate corresponding data vectors from the raw data for each data burst, and use machine learning to classify each data burst from the corresponding data vector. A method of classifying a data burst, comprising receiving an input waveform, extracting data bursts from the input waveform, deriving one or more spectral features of the data bursts, generating corresponding data vectors for each data burst from the one or more spectral features, and using machine learning to classify the data bursts from the corresponding data vectors.