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Accelerating the pace of engineering and science

 

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Abstracts

Driving Innovation with MATLAB and Simulink

Jim Tung, MathWorks Fellow and chief strategist

In this keynote talk, Jim Tung will present his perspectives on key technologies and trends that impact engineering and science. Jim will highlight trends in computational techniques, system development, and engineering analysis, including MathWorks technologies that are helping to drive innovation in these areas.

New Surface Fitting and Global Optimization Capabilities for Solving Challenging Data Analysis Problems

Eric Johnson, MathWorks

This presentation will show you how to overcome two common challenges with model fitting: developing good predictive models when you can’t describe the relationship between your variables, and estimating model parameters for nonlinear regression problems. We will demonstrate how to address these challenges using new capabilities in Global Optimization Toolbox, Statistics Toolbox™, and Curve Fitting Toolbox™.

Symbolic Computing with MATLAB and Simulink

Eric Johnson, MathWorks

This presentation will show how you can use symbolic computation with MATLAB and Simulink to support modeling, simulation, and embedded system design tasks. Using the notebook interface and other new features in Symbolic Math Toolbox™, we will develop an example wind turbine model, document it, and integrate it with MATLAB for design optimization studies.

Model-Based Design with MATLAB and Simulink – What’s New

Rick Rosson, MathWorks

This presentation will cover new developments, features, and capabilities in MATLAB and Simulink for using Model-Based Design for signal processing, communications, and controls applications. You’ll hear about developments such as the Embedded MATLAB® subset for generating embedded C code from MATLAB, PID control for automating control parameter selection, the Simscape™ language for physical system modeling, automatic code generation for FPGAs, and other new features and capabilities.

Introduction to Parallel Computing with MATLAB

Eric Johnson, MathWorks

This workshop will show you how MATLAB and MathWorks parallel computing tools enable you to solve computationally and data-intensive problems by taking advantage of recent advances in computer hardware, from multiprocessor machines to computer clusters. You will learn how to utilize multiple cores in your desktop machine through the new capabilities of MATLAB and Parallel Computing Toolbox™. We will also show how you can scale applications to computer clusters without changing the code.

Creating MATLAB Based Applications for MATLAB Users and Others

Eric Johnson, MathWorks

This workshop will demonstrate desktop and Web deployment of MATLAB applications. You’ll learn how you can distribute your MATLAB code directly to others to use in their own MATLAB applications, and how to create and distribute turnkey applications and components royalty-free to people who do not have MATLAB. These applications can be integrated into a larger IT infrastructure, such as the Web.

MATLAB to C for Embedded Applications

Rick Rosson, MathWorks

In this workshop, MathWorks engineers will demonstrate how using MATLAB code written with the Embedded MATLAB subset allows you to automatically generate C code directly from MATLAB for embedded software prototyping and implementation. We'll demonstrate how to use MATLAB and Fixed-Point Toolbox™ to develop embeddable floating-point and fixed-point algorithms and how to use Real-Time Workshop® to automatically generate C code directly from algorithms written in Embedded MATLAB code.

Simulink, Controls, and Real-Time Testing

Arkadiy Turevskiy, MathWorks

In this workshop, MathWorks engineers will demonstrate the use of Simulink and other products to design a real-time control system using a digital motion control case study. You will see how to:

  • Use dynamic simulation to verify and improve your design
  • Create plant models from experimental data and from first principles
  • Use test data to estimate model parameters
  • Design compensators using graphical tuning and optimization-based methods
  • Design and test fault detection logic
  • Conduct real-time model testing