Abstracts
Nurturing Innovation in Education
Andrew Clay, Managing Director of MathWorks Australia briefly looks at key technologies and trends that are impacting engineering and science, and how these trends are creating opportunities and challenges for educating and preparing the next generation of engineers and scientists.
Harnessing the Art of MATLAB for Teaching
This keynote presentation demonstrates how educators can use MATLAB and other MathWorks products interactively in classroom lecture and lab projects.
Educators in many disciplines start with a simple problem to illustrate techniques, and add complexity as students build their understanding and skills. This session starts with a problem that develops a student’s core skills in mathematics and physics, and is used in those domains as well as throughout engineering curricula. The demonstration includes a variety of approaches to solve the problem, allowing professors to choose the approaches that best match their domains of interest.
The second demonstration presents a more complex problem, showing how you can use symbolic computation with MATLAB and Simulink to support modelling, simulation, and embedded system design tasks. Using the notebook interface and other new features in Symbolic Math Toolbox, an example wind turbine model will be developed, documented, and integrated with MATLAB for design optimisation studies.
Introduction to Time-Domain Simulation with Simulink
This presentation introduces Simulink, a platform for multidomain simulation and Model-Based Design for dynamic and embedded systems. Unlike text-based programming languages such as C and C++, Simulink offers scientists and engineers the ability to model and simulate complex dynamic systems using a graphical block diagram syntax—a particularly elegant format for representing feedback loop patterns within a model. The Simulink simulation environment also provides both fixed-step and adaptive-step ODE solvers, all of which enable the modeller to focus on modelling the system of interest, rather than the underlying simulation framework needed to solve it. Once completed, these models can be automatically translated, via add-on products, to implementation languages such as C and HDL.
Product demonstrations provide a high-level overview of the major capabilities of Simulink and how it can be used for design, simulation, implementation, and test of complex dynamic systems. These demonstrations include examples from the communications, video processing, and physical system areas.
MATLAB for Signal Processing
This presentation provides an overview of major signal processing capabilities available in several MathWorks products. MATLAB and featured toolboxes enable users to more effectively solve problems encountered in analysis, design, implementation, and verification of signal processing systems.
Demonstrations show how you can use Signal Processing Toolbox, Filter Design Toolbox, Signal Processing Blockset, and related products to tackle a wide range of signal processing problems and challenges. Topics covered include:
- Spectral analysis
- Efficient signal processing techniques to handle live data and data streams
- Digital filter design
- C code generation from MATLAB using Embedded MATLAB functionality
Symbolic Computing and Statistical Modelling with MATLAB
This session explores the various techniques exercised by mathematicians, scientists, and analysts in industry for representing and solving problems using symbolic computing, statistical modelling, and optimisation.
You can use symbolic computing to find general solutions for complex technical problems that can quickly be evaluated for a wide range of conditions. Having a solution displayed symbolically not only ensures that your solution is exact but also gives you insight into the underlying mathematical structure of your problem.
The session starts with a demonstration using Symbolic Math Toolbox to conveniently manage and document symbolic computations.
The next part of this session demonstrates how to overcome common model fitting challenges with Statistics Toolbox, Curve Fitting Toolbox, and Global Optimization Toolbox. You can use these products to develop good predictive models when you can't describe the relationships between your variables and to estimate model parameters for nonlinear regression problems.
Lastly, a brief demonstration on optimisation problem solving highlights the capabilities of Optimization Toolbox and shows how to achieve faster execution time using Parallel Computing Toolbox.
Multidomain Physical Systems Modelling and Simulation
Are you currently looking for faster and easier ways of creating dynamic models of multidomain machines? Would you benefit if your model construction and simulation efforts focused less on deriving equations of motion and more on the structural representation of the complete system?
This presentation shows how to easily model multidomain systems within Simulink using Simscape and the physical modelling paradigm. Topics covered include:
- Efficiently modelling multidomain systems within the Simulink environment
- Creating new blocks or libraries using the Simscape language
- Fitting Simscape models into a system design workflow
The presentation includes a demonstration of the workflow from modelling through control system design of a hydromechanical system.
Introduction to Simulink for Signal Processing
This presentation introduces Simulink as a modelling environment for signal processing systems. Simulink extends MATLAB into a graphical, block-based development environment to simplify the modelling of dynamic systems. The session introduces key features in the Simulink product family (highlighting Signal Processing Blockset) that enable you to design systems in an integrated workflow. The presentation includes several demos that model audio, video, and communications systems, as well as a brief Simulink tutorial. Topics covered include frame-based processing, digital filter design, user-defined blocks (Embedded MATLAB functionality), multidomain modelling (RF/digital), rapid prototyping on DSPs, and HDL cosimulation. This presentation is targeted to those who are new to or unfamiliar with the Simulink environment; however, those with Simulink experience may still find the demos interesting and learn something new.
Advanced Programming Techniques in MATLAB
This master class illustrates the usage and explains the benefits of many of the function types available in MATLAB 7. Using the right function type can lead to more robust and maintainable code. Demonstrations will show how to apply these techniques to solve optimization problems and make it easier to program GUIs in MATLAB. This session also provides you with an understanding of how different MATLAB data types are stored in memory.
Image Processing in MATLAB
This master class discusses functionality for image processing in MATLAB and Image Processing Toolbox. Topics include:
- Image visualisation and graphics techniques
- Advanced indexing methods
- Computational tips and tricks for nonlinear filtering
- Creative binary image processing
- Image preprocessing options you may not know about