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.

公开(公告)号：US20180307584A1

公开(公告)日：2018-10-25

申请号：US15948923

申请日：2018-04-09

Applicant: Tektronix, Inc.

Inventor： Mark Anderson Smith ,  Michael Scott Silliman ,  Andrew Loofburrow ,  Eric T. Anderson

IPC: G06F11/36 ,  G06F8/41 ,  G06F9/445

CPC classification number: G06F11/3616 ,  G06F8/427 ,  G06F8/44 ,  G06F9/44521 ,  H03M5/12 ,  H03M7/04 ,  H03M7/28 ,  H04L25/4904

Abstract: Disclosed herein are systems and methods for converting physical input signals into bitstreams using syntax trees regardless of the physical input signal's protocol. Using declarative language definitions within a protocol declaration, a test and measurement system can compile a syntax tree that automatically translates the input data into a proper bitstream output. The declarative language definitions within the protocol declaration allow custom or standard protocol rules to be written for multiple or arbitrary input protocols without writing unsafe functions, having to access memory, or debugging more complex language codes.

公开(公告)号：US20240184637A1

公开(公告)日：2024-06-06

申请号：US18523556

申请日：2023-11-29

Applicant: Tektronix, Inc.

Inventor： John J. Pickerd ,  Sam J. Strickling ,  Mark Anderson Smith ,  Sunil Mahawar

IPC: G06F9/50 ,  G06F11/36

CPC classification number: G06F9/5077 ,  G06F11/362

Abstract: A machine learning management system includes a repository having one or more partitions, the one or more partitions being separate from others of the partitions, a communications interface, and one or more processors configured to execute code to: receive a selected model and associated training data for the selected model through the communications interface from a customer; store the selected model and the associated training data in a partition dedicated to the customer; and manage the one or more partitions to ensure that the customer can only access the customer's partition. A method includes receiving a selected model and associated training data for the selected model from a customer, storing the selected model and the associated training data in a partition dedicated to the customer in a repository, and managing the one or more partitions to ensure that the customer can only access the partition dedicated to the customer.

公开(公告)号：US20240126221A1

公开(公告)日：2024-04-18

申请号：US18482765

申请日：2023-10-06

Applicant: Tektronix, Inc.

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

IPC: G05B13/02

CPC classification number: G05B13/027

Abstract: A manufacturing system has a machine learning (ML) system having one or more neural networks and a configuration file associated with a trained neural network (NN), a structured data store having interfaces to the ML system a test automation application, a training store, a reference parameter store, a communications store, a trained model store, and one or more processors to control the data store to receive and store training data, allow the ML system to access the training data to train the one or more NNs, receive and store reference parameters and to access the reference parameters, receive and store prediction requests for optimal tuning parameters and associated data within the communication store, to provide requests to the ML system, allow the ML system to store trained NNs in the trained models store, and to recall a selected trained NN and provide the prediction to the test automation application.

公开(公告)号：US20220390515A1

公开(公告)日：2022-12-08

申请号：US17831181

申请日：2022-06-02

Applicant: Tektronix, Inc.

Inventor： John J. Pickerd ,  Mark Anderson Smith ,  Kan Tan ,  Evan Douglas Smith ,  Justin E. Patterson ,  Heike Tritschler

IPC: G01R31/3183 ,  G01R31/317

Abstract: A test and measurement system includes a machine learning system configured to communicate with a test automation system, a user interface configured to allow a user to provide one or more user inputs and to provide results to the user, and one or more processors, the one or more processors configured to execute code that causes the one or more processors to receive one or more user inputs through the user interface, the one or more user inputs at least identifying a selected machine learning system configuration to be used to configure the machine learning system, receive a waveform created by operation of a device under test, apply the configured machine learning system to analyze the waveform, and provide an output of predicted metadata about the waveform.

公开(公告)号：US20220268839A1

公开(公告)日：2022-08-25

申请号：US17681617

申请日：2022-02-25

Applicant: Tektronix, Inc.

Inventor： John J. Pickerd ,  Keith D. Rule ,  Mark Anderson Smith

IPC: G01R31/3183 ,  G01R31/317 ,  G01R31/319

Abstract: A test and measurement system includes a primary instrument having an input for receiving a test signal for measurement or analysis from a Device Under Test (DUT) and generating a test waveform from the test signal, and a duplicator for sending a copy of the test waveform to one or more secondary instruments. The one or more secondary instruments are each structured to access the copy of the test signal for analysis, and each of the one or more secondary instruments includes a receiver structured to receive a command related to measurement or analysis of the copy of the test waveform, one or more processes for executing the received command, and an output for sending results of the executed command to be displayed on a user interface that is separate from any user interface of the one or more secondary instruments.

公开(公告)号：US20210096971A1

公开(公告)日：2021-04-01

申请号：US17039691

申请日：2020-09-30

Applicant: Tektronix, Inc.

Inventor： Mark Anderson Smith ,  Byron T. Faber ,  Rohan Dhesikan ,  Kimberly Horton ,  Yurim Lee ,  Kathleen Elisabeth Smith

IPC: G06F11/26 ,  G06F11/22 ,  G06N20/00 ,  G06F13/20

Abstract: A test and measurement instrument includes a processor configured to execute instructions that cause the processor to: receive a bus auto-detect signal; receive signals from a bus connected to the test and measurement instrument; and apply machine learning to the signals from the bus to output a predicted a bus type; at least one memory to store the instructions and data used in the machine learning, and a display to display information for a user including the predicted bus type. A method of automatically detecting a bus type includes receiving a bus auto-detect signal when a bus is connected to a test and measurement instrument, receiving signals from the bus at a processor, and using the processor to apply machine learning to the signals from the bus to predict a bus identity.

公开(公告)号：US20210042212A1

公开(公告)日：2021-02-11

申请号：US16980375

申请日：2019-03-13

Applicant: Tektronix, Inc.

Inventor： Mark Anderson Smith ,  Michael Scott Silliman ,  Andrew Loofburrow ,  Eric T. Anderson

IPC: G06F11/36 ,  G06F8/60

Abstract: A protocol designer for a test and measurement instrument, comprising an input to receive a signal, a memory configured to store the signal, an author configured to generate protocol definitions based on a user input, a debugger configured to output textual and visual decode results based on the protocol definitions and the signal, and a deployer configured to output a complied protocol definition file to the test and measurement instrument.