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Solve Symbolic Equations Using Live Editor Tasks

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Solve Symbolic Equations Using Live Editor Tasks

Find analytical solutions of algebraic equations interactively by using the Solve Symbolic Equation task in the Live Editor with Symbolic Math Toolbox™. Solve Symbolic Equation task enables you to: - Solve a single equation and a system of algebraic equations - Specify the solver options and explore different solutions - Generate MATLAB® code used to solve equations for your live script. -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Using MATLAB with Python | Top Questions Answered

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Using MATLAB with Python | Top Questions Answered

Heather Gorr and Yann Debray walk through the ways you can use MATLAB and Python together. They answer questions about how to call Python libraries from MATLAB (and vice versa), package and deploy your MATLAB programs, and more. More Information: Overview of using MATLAB together with Python: https://bit.ly/3rw8rV7 GitHub link with resources: https://github.com/mathworks/matlab-with-python Cheat sheet for using MATLAB with Python: https://bit.ly/36kAUWp Blog post: https://bit.ly/2OsOCQe Documentation - Calling MATLAB from Python: https://bit.ly/3rKn4nA Data management: https://bit.ly/2OvJ5Z9 Additional Videos: How to Call MATLAB from Python: https://www.youtube.com/watch?v=OocdPu1Tcrg How to Call Python from MATLAB: https://www.youtube.com/watch?v=LHEZqpvE7D0&t=0s First live stream recording: https://www.youtube.com/watch?v=y7NBT6O0fJU

MathWorks
Integrating RoadRunner with MATLAB and Simulink

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Integrating RoadRunner with MATLAB and Simulink

This video walks through steps that are required to connect RoadRunner™ and MATLAB® and Simulink® via Unreal Engine. You will learn how to set up the platforms and plugins required to enable a user to create a graphically detailed scene in RoadRunner, import the scene into MATLAB and Simulink using the Automated Driving Toolbox™ Driving Scenario Designer app, and connect to Epic Games Unreal Engine to test your autonomous vehicle algorithms and simulation. This workflow enables the user to test their algorithms in a dynamic and detailed environment that can be created within minutes. For more information, refer the Highway Lane Following with RoadRunner Scene example: https://bit.ly/3orCmMT Additional Resources: - Highway Lane Following with RoadRunner Scene: https://bit.ly/3orCmMT -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Efficient Design with SerDes and Export IBIS-AMI Model

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Efficient Design with SerDes and Export IBIS-AMI Model

This example shows how to use the SerDes Designer app to create and analyze a SerDes system, and create the IBIS-AMI models for the transmitter and receiver from Simulink®. In this example, you can learn how to design the top-level SerDes system in the app, then export a Simulink model for further time-domain analysis. Finally, you can export the IBIS-AMI models for the finalized SerDes system from Simulink. Additional Resources: - SerDes Toolbox: https://bit.ly/3bfvu1t - SerDes Toolbox Design Examples: https://bit.ly/2L9BZZ0 - SerDes Design Videos: https://bit.ly/3onCfC2 -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Modeling and Simulation in Drug Development with SimBiology

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Modeling and Simulation in Drug Development with SimBiology

This webinar introduces SimBiology as a modeling environment for mechanistic pharmacokinetic (PK), pharmacodynamic (PD), and quantitative systems pharmacology (QSP) modeling and simulation. Additional Resources: - SimBiology Tutorials for QSP, PBPK, and PK/PD Modeling and Analysis: https://bit.ly/3nehya8 -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Developing Radio Applications for RFSoC, Part 3: Hardware/Software Partitioning

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Developing Radio Applications for RFSoC, Part 3: Hardware/Software Partitioning

See the full playlist here: https://www.youtube.com/playlist?list=PLn8PRpmsu08qnuOlFZTVKLRir_uEIZKJX Perform simulation and analysis of the SoC architecture of the Xilinx® RFSoC to investigate hardware/software partitioning of the range-Doppler radar algorithm. In this third video in the series, learn how to develop a Simulink® model that serves as a reference for verifying implementation models. See how to analyze the algorithm’s memory requirements to determine whether external DDR4 memory is required for hardware implementation. Then learn how to evaluate two candidate hardware/software partitioning alternatives by comparing the effects of performing the FFT operation in the quad-core Arm® Cortex®-A53 processor versus performing the FFT in programmable logic. Explore how to model the DDR4 memory transactions using Memory Controller and Traffic Generator blocks of SoC Blockset™, and use simulation to determine the latency of memory write and read operations. Pre-characterized models for the Xilinx ZCU111 development board enable accurate evaluation of latency using simulation, without the need for hardware testing. Then using processor-in-the-loop (PIL) testing, you can perform on-device profiling and measurement of latency for the algorithm running on the processor. These techniques allow you to determine the latency and implementation complexity of each option so you can decide on an approach that best meets requirements. In Part 4 of this video series, you will see how SoC Blockset drives the process of generating a complete hardware/software application and deploying it to the ZCU111 development board. Additional Resources: - Trial request - SoC Blockset: https://bit.ly/3oteKY7 -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Generate Floating-Point HDL for FPGA and ASIC Hardware

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Generate Floating-Point HDL for FPGA and ASIC Hardware

Quantizing floating-point algorithms to fixed-point for efficient FPGA or ASIC implementation requires many steps and numerical considerations. Converging on the right balance between arithmetic precision and hardware resource usage is an iterative process between algorithm and hardware design. The process becomes more difficult when it requires a high-precision or high-dynamic range. To simplify this process, HDL Coder™ can generate target-independent synthesizable VHDL® or Verilog® from single-, double-, or half-precision floating-point algorithms for FPGA or ASIC deployment. This overview shows how to generate floating-point FPGA and ASIC hardware, including: - How to identify algorithms that might benefit from staying in floating-point - What types of operations HDL Coder native floating-point code generation supports - How to mix fixed- and floating-point implementation in the same design using Fixed-Point Designer™ - How to control latency and sharing optimizations for native floating-point code generation to meet your FPGA or ASIC implementation goals Additional Resources: - Request a Free Trial: https://bit.ly/3iMPt9A - Learn more about HDL Coder pipeline insertion and oversampling: https://bit.ly/3sRP4XT - Learn how DEMCON reduced their FPGA development time using HDL Coder native floating-point: https://bit.ly/36dsUFY -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Developing Radio Applications for RFSoC, Part 2: System Specification and Design

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Developing Radio Applications for RFSoC, Part 2: System Specification and Design

Check out the full playlist: https://www.youtube.com/playlist?list=PLn8PRpmsu08qnuOlFZTVKLRir_uEIZKJX System specifications for a range-Doppler radar are the driver for hardware/software implementation decisions when targeting SoC architectures like Xilinx® RFSoC devices. In this second video in the series, see how specifications like peak bandwidth, range, and pulse rates serve as the basis for making implementation designs. Review the process of frequency planning, which includes setting parameters such as intermediate frequency (IF), sampling rate (Fs), NCO mixer frequency, decimation/interpolation factor, and FPGA clock rate. Find out how to use simulation in Simulink® to validate the RF-ADC digital down conversation chain. Once the DDC chain is validated, learn how you can use the simulation of the complete system—with models of radar targets, range-Doppler radar processing, and detection—to determine whether targets are being detected. The resulting behavioral simulation model serves as the basis for hardware/software partitioning in part 3 of this video series. Additional Resources: - Trial request: SoC Blockset™: https://bit.ly/3oteKY7 -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
MATLAB Grader Overview

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MATLAB Grader Overview

Create autograded MATLAB® assignments using MATLAB Grader. Build MATLAB coding problems and store them in collections. Host courses for students on MATLAB Grader, or include MATLAB based assignments in your Learning Management System based course. Additional Resources: - MATLAB Grader: https://bit.ly/3a6GPi5 -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
How to Perform Data Labeling for Camera and Lidar Sensor Data

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How to Perform Data Labeling for Camera and Lidar Sensor Data

Data labeling with the Ground Truth Labeler app enables you to label camera and lidar data. Using the app interface, you can label data manually or use algorithms in MATLAB® to automate the data labeling process. Once the process is complete, you can use the data to train deep learning and machine learning models or to validate ADAS algorithms. -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Developing Radio Applications for RFSoC, Part 1: Hardware/Software Co-Design Workflow

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Developing Radio Applications for RFSoC, Part 1: Hardware/Software Co-Design Workflow

This is part one of a series. Stay tuned for parts 2 and 3. Target SoC architectures like Xilinx® UltraScale+™ RFSoC devices using Model-Based Design. With the workflow featured in this video, you can evaluate how algorithms will perform on hardware/software platforms such as Xilinx RFSoC development boards. This first video in the series, learn about Xilinx UltraScale+ RFSoC devices and their applications in wireless communications, aerospace and defense, and test and measurement. Discover a new workflow spanning modeling and simulation through application deployment. An example of hardware/software coprocessing illustrates the design choices required to develop algorithms for the RFSoC hardware/software platform and lists the hardware boards supported by this workflow. Additional Resources: - Trial request - SoC Blockset: https://bit.ly/3oteKY7 -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Deep Learning with Raspberry Pi and MATLAB

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Deep Learning with Raspberry Pi and MATLAB

Learn how to use MATLAB® along with a Raspberry Pi™ to develop, test and deploy a deep learning network using a computer vision example. Do you want to take your deep learning algorithms beyond desktop and apply them in real-world systems? In this webinar, we will show how MATLAB can be used to deploy your deep learning algorithms onto a Raspberry Pi. We will also talk about the new C++ code generation capability for Raspberry Pi functions that allows you to easily interface with the trained deep neural networks on the Raspberry Pi while performing prediction tasks. We will use a real-world computer vision example to demonstrate how to deploy deep learning networks and perform inference tasks on your embedded hardware. Highlights: Generate C/C++ code from deep learning networks as inference engines for Raspberry Pi. Access peripherals from the Raspberry Pi for use in MATLAB with the generated code. Additional Resources: Learn more about MATLAB Coder: https://bit.ly/3pnmD1N -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
How to Perform Curve Fitting Using the Curve Fitting App in MATLAB

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How to Perform Curve Fitting Using the Curve Fitting App in MATLAB

Learn how to perform curve fitting in MATLAB® using the Curve Fitting app, and fit noisy data using smoothing spline. This video shows you how to use the Curve Fitting app to interactively try a variety of fitting algorithms, assess the fit numerically, and generate code from the app. See the Curve Fitting Toolbox™ product page: https://bit.ly/360ypHL Learn more about the Curve Fitting app: https://www.mathworks.com/products/curvefitting.html#app Learn more about smoothing splines: https://bit.ly/3qBoYXe -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
What Is a CAN Bus?

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What Is a CAN Bus?

Learn how a Controller Area Network Bus (CAN Bus) operates as well as its applications in different industries. This video covers how a CAN Bus connects nodes and ECUs in a single system and the specific protocols that define different CAN operations. It also highlights how traditional CAN differs from CAN Flexible Data Rate (CAN FD). You can use MATLAB®, Simulink®, and Vehicle Network Toolbox™ to directly interface with your CAN Bus and develop applications that: - Support hardware manufacturers such as Kvaser, NI®, PEAK-System, and Vector - Collect raw CAN data, process the data using DBC files, and visualize the results in a single environment - Utilize the CAN Tool to work directly with your CAN Bus in an application without having to write MATLAB code - Implement higher-level protocols such as XCP and J1939 to define CAN operations for specific applications - Convert into C or C++ code and deploy to embedded targets Additional Resources: - Vehicle Network Toolbox: https://bit.ly/3byxNgf -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Getting Started with Stateflow

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Getting Started with Stateflow

Discover the basics of using Stateflow® by walking through an example. You will learn how to model, simulate, and test a supervisory controller that determines whether a building uses energy stored in a battery or energy from the electric grid. You’ll also see how to build a state diagram from scratch, connect states with conditional transitions, add flow chart decision logic, and then run simulations with animation to ensure that the model is working correctly. After going through the example, you’ll learn how Stateflow is just one part of Model-Based Design for modeling, simulating, testing, and implementing real-world systems. Additional Resources: - Download ebook: https://bit.ly/3i9vilV - Learn the essentials of Stateflow through the Stateflow Onramp: https://bit.ly/3byIJKF - Get more info about Stateflow: https://bit.ly/2M6smut -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
What Is MATLAB Compiler?

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What Is MATLAB Compiler?

MATLAB Compiler™ enables you to share MATLAB® programs as standalone applications, web apps, and Docker container images. Check out more on MATLAB Compiler: https://bit.ly/3chL8ts With MATLAB Compiler, you can also package and deploy MATLAB programs as MapReduce and Spark™ big data applications or as Microsoft® Excel® Add-ins. End users can run your applications royalty-free with MATLAB Runtime or embed them directly within your compiled applications. MATLAB Runtime is a set of shared libraries required to run artifacts generated with MATLAB Compiler, which is free to download from mathworks.com. You can generate different targets using MATLAB Compiler such as the standalone application, which you can create from MATLAB programs or from apps developed using MATLAB App Designer. Use the Application Compiler to package the main file and any associated files into the installer. You can also customize your application with a unique startup image and provide additional text information. Then, package your files and provide the generated installer to your end users, who can install and run it like any other desktop application. Using the development version of MATLAB Web App Server™ included with MATLAB Compiler, you can develop and test out the web apps workflow. Users interact with web apps in a browser without needing to install any additional software. As your MATLAB apps require further capabilities, such as authentication, you can adopt the MATLAB Web App Server product, which also supports interacting with apps created from different MATLAB releases. You can package and distribute your standalone applications as self-contained Docker images. The container image consists of the application, optimized MATLAB Runtime components, and operating system libraries. Additionally, you can create custom functions for Microsoft Excel by packaging MATLAB programs as Excel Add-ins. Excel users access these custom functions just as they would with any native function to perform analyses. With MATLAB Compiler, you can generate standalone applications, web apps, and other targets that fit your deployment needs to distribute your applications to users whether or not they have MATLAB and Simulink®. For more information, please visit the MATLAB Compiler product page or contact a sales representative for a trial. -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Design Lidar-Based SLAM Using Unreal Engine Simulation Environment

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Design Lidar-Based SLAM Using Unreal Engine Simulation Environment

Record and visualize synthetic lidar sensor data from the Unreal Engine® simulation environment. Then develop a perception algorithm to build a map using SLAM in MATLAB®. -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
How to Implement Units of Measurement in MATLAB

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How to Implement Units of Measurement in MATLAB

This video outlines the essential concepts behind the use of units in MATLAB® in such a way that they can be accessible to every user - from beginner to advanced. All the examples shown are related to the force formula, and the main command you can use to declare units is symunits. The video emphasizes the concept that units in MATLAB are symbolic variables and that they remain symbolic variables even when operations are performed, adopting numeric values and other symbolic variables. The video also explains the behavior of various functions, including newUnit, rewrite, unitInfo, checkUnits, unitConvert, vpa, separateUnits. For each of these functions, the video also shows the required types of inputs and the generated kind of outputs This video was created as part of the MATLAB student ambassador program: https://bit.ly/36BoXdE Additional Resources: Learn more about using symbolic math for your applications: https://bit.ly/39PozK2 Documentation for built-in units in MATLAB: https://bit.ly/3p2Iw6l Check out a MATLAB example: https://bit.ly/3qDFaay https://bit.ly/39PozK2 -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Motor Control, Part 5: Space Vector Modulation

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Motor Control, Part 5: Space Vector Modulation

Space vector modulation (SVM), also known as space vector pulse width modulation (SVPWM), is a common technique in field-oriented control for induction and permanent magnet synchronous motors (PMSM). See the full playlist with all videos: https://www.youtube.com/playlist?list=PLn8PRpmsu08qL-EG3DRMtRyokpXQJyhp7 SVM generates the pulse width modulated (PWM) signals to control the switches of a three-phase inverter, which then generates the three-phase voltages required to drive the motor at a desired speed or torque. Learn how SVM generates a voltage vector at any given angle and magnitude by alternating between basic and null vectors. This video also compares space vector modulation to sinusoidal PWM, which is another commonly used method for motor control. SVM lets you fully utilize the DC source voltage and increases bus utilization by 13.3% over sinusoidal PWM. Additional Resources: - Space Vector Modulation for Motor Control: https://bit.ly/3oQktra - Motor Control Design with Simulink: https://bit.ly/35DVHTN - Develop field-oriented control algorithms using simulation: https://bit.ly/3bKrfeq -------------------------------------------------------------------------------------------------------- Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2019 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Functions with Multiple Inputs or Outputs | Managing Code in MATLAB

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Functions with Multiple Inputs or Outputs | Managing Code in MATLAB

Learn how to create MATLAB® functions with multiple inputs and outputs, and get an overview of the topic. See all MATLAB blog posts: https://bit.ly/2LV3sxp Get more info about MATLAB: https://bit.ly/2XFZknN -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
What Are Functions in MATLAB? | Managing Code in MATLAB

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What Are Functions in MATLAB? | Managing Code in MATLAB

Get an overview of the topic, and learn about what functions are in MATLAB®. See all MATLAB blog posts: https://bit.ly/2LV3sxp Get more info about MATLAB: https://bit.ly/2XFZknN -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Deploy Motor Control Algorithms to FPGA – Overview

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Deploy Motor Control Algorithms to FPGA – Overview

Motor control and power systems engineers are starting to use FPGAs and SoCs in their designs, which are getting more complex and computationally demanding in areas like electric vehicles, multi-axis robots, etc. In this short video, see how you can use Simulink® to program FPGAs and SoCs even when engineers have little to no expertise in FPGA programming. Additional Resources: - Request HDL Coder Trial: https://bit.ly/39e5Qax - How Modeling and Simulation bring Algorithm Development and SoC Design Together: https://bit.ly/2MLrjAg -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

MathWorks
Execution Order for AUTOSAR Runnables in Simulink

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Execution Order for AUTOSAR Runnables in Simulink

The AUTOSAR Timing Extensions specification defines execution order constraints. These constraints specify the execution order of runnable entities within a component. In Simulink, you can: - Import execution order constraints from ARXML files. - Open an AUTOSAR component model and use the Schedule Editor to modify the execution order of runnables. - Export execution order constraints to ARXML files. - Update execution order constraints in an AUTOSAR component model by importing ARXML changes. In an AUTOSAR software component model, you can use the Schedule Editor to schedule and specify the execution order of runnables. The Schedule Editor is a scheduling tool that displays partitions in a model, the data connections between them, and the order of those partitions. In AUTOSAR component models, partitions correspond to runnable entities that execute independently. In the Schedule Editor, you can: - View a graphical representation of runnables as partitions in an AUTOSAR component. - Create partitions and map them to AUTOSAR runnables. - Directly specify the execution order of runnables. The Schedule Editor supports multiple modeling styles, including rate-based and export-function modeling. For more information, see Using the Schedule Editor and Create Partitions. -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2020 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

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Model-Based Design with MATLAB and Simulink

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Model-Based Design with MATLAB and Simulink

Use Model-Based Design with MATLAB® and Simulink® to easily try out new ideas, expose design problems early, automate steps such as code generation, and speed up the overall development process by 50% or more. Learn more about Simulink: https://bit.ly/3rScVGo Download the white paper "Model-Based Design for Embedded Control Systems": https://bit.ly/2Xd70xD -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2021 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

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Labeling Signals for AI Tasks with Signal Labeler App

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Labeling Signals for AI Tasks with Signal Labeler App

The Signal Labeler app lets you label attributes, regions of interest, and points in signals to get the data ready for AI applications. -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2020 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

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