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    POWER VECTOR ANALYZER
    51.
    发明申请
    POWER VECTOR ANALYZER 有权

    公开(公告)号：US20250130279A1

    公开(公告)日：2025-04-24

    申请号：US18914685

    申请日：2024-10-14

    Applicant: Tektronix, Inc.

    Inventor： John J. Pickerd

    IPC: G01R31/319 ,  G01R27/28 ,  G01R35/00

    Abstract: A power vector analyzer to analyze power from a device under test (DUT) includes one or more channels to measure a reference voltage signal from a power line connected to the DUT, one or more channels to measure a reference current signal from the power line, a user interface comprising a display and one or more controls, and a quadrature synchronous detector (QSD) for each phase of apparent power being measured, the QSD configured to use a reference voltage signal from the one or more channels and a reference current signal from the one or more channels to determine the apparent power for each phase of power being measured by the DUT and display the apparent power for each phase on the display.

    SYSTEM AND METHOD FOR DECIMATED SWEEP MEASUREMENTS OF A DEVICE UNDER TEST USING MACHINE LEARNING
    52.
    发明申请
    SYSTEM AND METHOD FOR DECIMATED SWEEP MEASUREMENTS OF A DEVICE UNDER TEST USING MACHINE LEARNING 有权

    公开(公告)号：US20250102573A1

    公开(公告)日：2025-03-27

    申请号：US18829842

    申请日：2024-09-10

    Applicant: Tektronix, Inc.

    Inventor： John J. Pickerd ,  Kan Tan ,  Jamel Benbrik

    IPC: G01R31/3183 ,  G01R31/319

    Abstract: A test and measurement instrument includes one or more ports to allow the test and measurement instrument to receive a signal from a device under test (DUT), a user interface to allow the user to send inputs to the test and measurement instrument and receive results, and one or more processors configured to acquire the signal from the DUT, make measurements on the signal to create a decimated measurement set, convert the decimated measurement set into a tensor, send the tensor to a machine learning network, and receive a pass/fail value from the machine learning network. A method includes acquiring a signal from a device under test (DUT), making measurements on the signal to create a decimated measurement set, convert the decimated measurement set into a tensor, sending the tensor to a machine learning network, and receiving a pass/fail value from the machine learning network.

    MULTIPLE PULSE EXTRACTION FOR TRANSMITTER CALIBRATION
    53.
    发明申请
    MULTIPLE PULSE EXTRACTION FOR TRANSMITTER CALIBRATION 有权

    公开(公告)号：US20250004014A1

    公开(公告)日：2025-01-02

    申请号：US18754871

    申请日：2024-06-26

    Applicant: Tektronix, Inc.

    Inventor： Kan Tan ,  David M. Bouse ,  John J. Pickerd

    IPC: G01R13/02 ,  G01R31/28 ,  G01R31/317

    Abstract: A test and measurement instrument has a port to receive a signal from a device under test (DUT), one or more processors configured to execute code that causes the one or more processors to acquire a waveform from the signal, derive a pattern waveform from the waveform using one of either hardware or software clock recovery, perform linear fit pulse response (LFPR) extractions on the pattern waveform to extract more than one LFPR, determine a reference pulse response from the more than one LFPRs, compare at least one of the LFPRs to the reference pulse response to determine a difference, and tune the DUT to reduce the difference. The test and measurement instrument may also use the multiple LFPRs as an input to a machine learning network to perform measurement predictions for the DUT.

    SYSTEM AND METHOD FOR DEVELOPING MACHINE LEARNING MODELS FOR TESTING AND MEASUREMENT
    55.
    发明申请
    SYSTEM AND METHOD FOR DEVELOPING MACHINE LEARNING MODELS FOR TESTING AND MEASUREMENT 有权

    公开(公告)号：US20230098379A1

    公开(公告)日：2023-03-30

    申请号：US17951064

    申请日：2022-09-22

    Applicant: Tektronix, Inc.

    Inventor： Mark Anderson Smith ,  Sunil Mahawar ,  John J. Pickerd ,  Sriram K. Mandyam

    IPC: G06N20/00 ,  G06K9/62 ,  G06N3/02

    Abstract: A test and measurement machine learning model development system includes a user interface, one or more ports to allow the system to connect to one or more data sources, one or more memories, and one or more processors configured to execute code to cause the one or more processors to: display on the user interface one or more application user interfaces, the application user interfaces to allow a user to provide user inputs; use and application programming interface to configure the system based on the user inputs; receive data from the one or more data sources; apply one or more modules from a library of signal processing and feature extraction modules to the data to produce training data; apply one or more machine learning models to the training data; provide monitoring of the one or more machine learning models; and save the one or more machine learning models to at least one of the one or more memories. A method for operating a machine learning model development system includes displaying, on a user interface, one or more application user interfaces, the application user interfaces allowing a user to provide user inputs, configuring the system based on the user inputs through an application programming interface, receiving data from one or more data sources, applying one or more modules from a library of signal processing and feature extraction modules to the data to produce training data, applying one or more machine learning models to the training data, providing monitoring of the one or more machine learning models, and saving the one or more machine learning models to at least one of the one or more memories.

    Low frequency S-parameter measurement
    56.
    发明授权
    Low frequency S-parameter measurement 有权

    公开(公告)号：US11598805B2

    公开(公告)日：2023-03-07

    申请号：US16888443

    申请日：2020-05-29

    Applicant: Tektronix, Inc.

    Inventor： John J. Pickerd ,  Kan Tan

    IPC: G01R31/317

    Abstract: A method determines scattering parameters, S-parameters, for a device under test for a first frequency range. The method includes receiving S-parameters for the device under test for a second frequency range, the second frequency range greater than the first frequency range. Generally, the S-parameters for the device under test for the second frequency range can be determined using known methods. The method further includes measuring an actual response of the device under test, determining a desired signal of the device under test, and determining the S-parameters for the device under test for the first frequency range based the S-parameters for the second frequency range, actual response of the device under test and the desired signal of the device under test.

    OPTICAL TRANSCEIVER TUNING USING MACHINE LEARNING
    57.
    发明申请
    OPTICAL TRANSCEIVER TUNING USING MACHINE LEARNING 有权

    公开(公告)号：US20220311514A1

    公开(公告)日：2022-09-29

    申请号：US17701411

    申请日：2022-03-22

    Applicant: Tektronix, Inc.

    Inventor： Evan Douglas Smith ,  John J. Pickerd ,  Williams Fabricio Flores Yepez ,  Heike Tritschler

    IPC: H04B10/079 ,  H04B10/077

    Abstract: A test and measurement device has a connection to allow the test and measurement device to connect to an optical transceiver, one or more processors, configured to execute code that causes the one or more processors to: initially set operating parameters for the optical transceiver to average parameters, acquire a waveform from the optical transceiver, measure the acquired waveform and determine if operation of the transceiver passes or fails, send the waveform and the operating parameters to a machine learning system to obtain estimated parameters if the transceiver fails, adjust the operating parameters based upon the estimated parameters, and repeat the acquiring, measuring, sending, and adjusting as needed until the transceiver passes. A method to tune optical transceivers includes connecting a transceiver to a test and measurement device, setting operating parameters for the transceiver to an average set of parameters, acquiring a waveform from the transceiver, measuring the waveform to determine if the transceiver passes or fails, sending the waveform and operating parameters to a machine learning system when the transceiver fails, using the machine learning system to provide adjusted operating parameters, setting the operating parameters to the adjusted parameters, and repeating the acquiring, measuring, sending, using, and setting until the transceiver passes.

    OPTICAL TRANSMITTER TUNING USING MACHINE LEARNING AND REFERENCE PARAMETERS
    58.
    发明申请
    OPTICAL TRANSMITTER TUNING USING MACHINE LEARNING AND REFERENCE PARAMETERS 有权

    公开(公告)号：US20220311513A1

    公开(公告)日：2022-09-29

    申请号：US17701186

    申请日：2022-03-22

    Applicant: Tektronix, Inc.

    Inventor： John J. Pickerd ,  Kan Tan ,  Evan Douglas Smith ,  Heike Tritschler

    IPC: H04B10/077 ,  H04B10/40

    Abstract: A test and measurement system includes a test and measurement device, a connection to allow the test and measurement device to connect to an optical transceiver, and one or more processors, configured to execute code that causes the one or more processors to: set operating parameters for the optical transceiver to reference operating parameters; acquire a waveform from the optical transceiver; repeatedly execute the code to cause the one or more processors to set operating parameters and acquire a waveform, for each of a predetermined number of sets of reference operating parameters; build one or more tensors from the acquired waveforms; send the one or more tensors to a machine learning system to obtain a set of predicted operating parameters; set the operating parameters for the optical transceiver to the predicted operating parameters; and test the optical transceiver using the predicted operating parameters.

    SYSTEM AND METHOD FOR MULTI-LEVEL SIGNAL CYCLIC LOOP IMAGE REPRESENTATIONS FOR MEASUREMENTS AND MACHINE LEARNING
    59.
    发明申请
    SYSTEM AND METHOD FOR MULTI-LEVEL SIGNAL CYCLIC LOOP IMAGE REPRESENTATIONS FOR MEASUREMENTS AND MACHINE LEARNING 有权

    公开(公告)号：US20210389373A1

    公开(公告)日：2021-12-16

    申请号：US17345312

    申请日：2021-06-11

    Applicant: Tektronix, Inc.

    Inventor： John J. Pickerd ,  Fabricio Flores

    IPC: G01R31/319 ,  G06N20/00

    Abstract: A system includes an input to receive a digital waveform signal, a memory, and one or more processors configured to execute code to cause the one or more processors to: generate a horizontal ramp sweep signal based on the digital waveform signal; receive a selection input to identify a segment of the digital waveform signal; gate the horizontal ramp sweep signal and the digital waveform signal based on the selection input to produce cyclic loop image data for the segment of the digital waveform; store the cyclic loop image data in the memory; and provide the cyclic loop image data as one or more inputs into a machine learning system. A method of waveform classification using a cyclic loop image includes receiving an input waveform, receiving a selection of a segment of the input waveform, transforming the segment of the input waveform into cyclic loop image data, the transforming comprising generating a horizontal ramp sweep signal based on edge transitions in the input waveform, and storing the cyclic loop image data in a memory; and sending the cyclic loop image data to a machine learning system to determine an attribute of the input waveform.

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