Visit the demo stations to discuss your challenges and ideas with MATLAB® and Simulink® experts, and see demos showcasing the latest features in MATLAB and Simulink.
MATLAB makes deep learning easy and accessible even if you are not an expert. Learn how you can perform deep learning tasks with just a few lines of code. Also discover how you can design and build your own convolutional neural network models, access the latest models, or import pretrained models.
Computationally intensive MATLAB code for deep learning, computer vision, and autonomous systems can be accelerated using GPUs on your development computer. Learn and discuss how you can do this, and also generate optimized CUDA® code from your MATLAB code to deploy your algorithms onto embedded GPU hardware.
Engineering and IT teams use MATLAB to build advanced data analytics systems such as predictive maintenance. Discuss and understand how you can bring in and manage physical-world data and apply machine learning, neural networks, and statistics.
MATLAB and Simulink applications can be scaled up with clusters and clouds. Learn and understand how you can use parallel computing tools to accelerate computationally intensive MATLAB programs by running them in large-scale, high-performance computing resources such as computer clusters and cloud computing services (e.g. Amazon EC2® and Microsoft® Azure®).
Verilog® and VHDL can be generated from designs in MATLAB and Simulink. Additionally, hardware-software co-design is enabled by providing C/C++ code generation for your software models. Discuss and learn how you can design and generate code and additionally leverage targeted support for popular development boards such as Xilinx® Zynq®-7000, and Intel® Cyclone V SoC.
5G enables the next generation of wireless communications: gigabit data rates, improved coverage, low latency, and increased connectivity for machines and vehicles. Learn about the support for 5G waveforms in MATLAB, and about the technologies to simulate practical 5G implementations, including hybrid beamforming architectures with massive antenna arrays.
Automated driving spans a wide range of automation levels, from advanced driver assistance systems (ADAS) to fully autonomous driving. Learn and discuss how MATLAB® and Simulink® support designing automated driving system functionality, including computer vision algorithm development, sensor fusion, and controls development. Find out how the latest capabilities for vehicle dynamics modelling support the simulation and verification of these systems.
Systems are becoming more and more complex with multiple physical domains interacting. The software domain is a major portion of modern systems and needs to be taken into account as well. Learn and discuss how Simulink provides a complete simulation environment that lets you integrate multiple physical domains and control software to capture the behaviour of the full system.
Designs (models) of control software and physical systems in Simulink can be reused for the purpose of real-time testing. Learn and discuss how you can move from pure desktop simulation to real-time execution of your models on hardware specifically designed and optimized for rapid prototyping or hardware-in-the-loop (HIL) simulations.
Early verification on the model level, and later on the code level, to ensure correctness of model and code are strategic activities within Model-Based Design. Learn and discuss capabilities such as model checking, coverage measurement, requirements management, and static analysis at the code level to increase the quality of your design. Understand how Model-Based Design with MATLAB and Simulink supports compliance with your safety standard, such as ISO 26262, DO-178C, and other standards.