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

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

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

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

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.

MATLAB to C for Embedded Applications

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.

Computer Vision and Video Processing in MATLAB

R2010a introduced new algorithms and tools that enable computer vision and video processing directly from within MATLAB. New technology called System objects, available in Video and Image Processing Blockset™, extends MATLAB and Image Processing Toolbox™ with the ability to process streaming data. In this workshop, we will demonstrate new tools for video I/O and display and new algorithms for video processing and computer vision.

Configuring Plant Models for Real-Time Simulation

Using models built using MathWorks physical modeling products, this workshop will outline the steps in moving multidomain system models from desktop simulation to real-time simulation. Real-time simulation of multidomain physical system models (mechanical, electrical, hydraulic, and so forth) requires finding a combination of model complexity, solver choice, solver settings, and real-time target that permits execution in real time. A better understanding of the tradeoffs involved in each of these areas makes it easier to achieve this goal and to use Model-Based Design to reap the benefits of using virtual systems prior to building hardware prototypes.