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Technical Computing with MATLAB and Simulink at Columbia University

Join MathWorks for free MATLAB seminars on Thursday, September 30, and Friday, October 1, at Columbia University. Three sessions will be offered. You can register for any or all of the following sessions:

  • Data Analysis and Visualization in MATLAB (September 30)
  • Designing and Modeling a Multidomain System in MATLAB and Simulink (September 30)
  • Speeding Up Applications: Parallel Computing with MATLAB (October 1)

All seminar sessions will be held at:

Davis Auditorium
412 CEPSR Building (Morningside Campus)
Columbia University

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Terri Xiao, MathWorks Application Engineer

Data Analysis and Visualization in MATLAB

Thursday, September 30
10:00 a.m.–12:00 p.m.

In this session we introduce specific examples to demonstrate how to acquire, analyze, and visualize data through mathematical, statistical, and engineering functions that support common engineering operations. The provides an overview of the MATLAB technical computing environment, including desktop tools for editing and debugging code, publishing your work, programming and 3D visualization, and creating graphical user interfaces (GUI). We incorporate a number of new features from the latest version of MATLAB.

Highlights include:

  • Importing data into MATLAB
  • Performing statistical analysis and curve fitting
  • Automating analysis via automatic MATLAB code generation
  • Building GUIs and generating reports


Designing and Modeling a Multidomain System in MATLAB and Simulink

Thursday, September 30
1:00–3:30 p.m.

This session demonstrates how to develop an algorithm in MATLAB that you can incorporate into a dynamic system using Simulink. We develop an object tracking algorithm in MATLAB and then use Simulink to design and model the mechanical and electrical components of the motor. We also show how to design and automatically tune the controller to optimize system performance and, finally, implement the system on real-time hardware.

Highlights include:

Developing an Algorithm in MATLAB
Case study: Data/image acquisition and analysis

  • Accessing data (from files or hardware)
  • Analyzing and visualizing data in MATLAB
  • Publishing and deploying the results

Modeling and Controlling a System in Simulink
Case study: Object tracking mechanism

  • Realizing the MATLAB algorithm for real-world use
  • Modeling and simulating the electromechanical dynamic system
  • Performing feedback control design and optimization
  • Automatically generating code for prototyping

Speeding Up Applications: Parallel Computing with MATLAB

Friday, October 1
10:00 a.m.–12:00 p.m.

In this session we demonstrate how to perform parallel and distributed computing in MATLAB to boost execution speed on computationally intensive problems, including how to handle larger data sets. We highlight our add-on tools that offer built-in ability to take advantage of parallel computing resources without requiring any extra coding. We introduce you to parallel processing constructs such as parallel for-loops, distributed arrays, and message-passing functions that allow you to convert serial MATLAB applications to parallel MATLAB applications with few code modifications. You’ll see how you can:

  • Leverage toolboxes with built-in support for parallel computing
  • Go faster using task-parallel processing
  • Work with larger data sets using data-parallel processing
  • Scale up to a cluster: interactive to scheduled jobs
  • Develop parallel code

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