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In this workshop, you will learn about the Model-Based Design workflow using HLS block set of Model Composer, how to set up the Simulink model using blocks from HLS library, and do automatic code generation.

In this workshop, you will learn about the Versal™ adaptive SoC and the architecture of the AI Engine, the various interfaces available in the AI Engine tile, Versal AI Engine Tool Flow and Vitis Model Composer for AI Engine Design.

Join us for a hands-on workshop session where we will demonstrate the workflows offered by MATLAB and Simulink. From data-driven, AI-based solutions to technical and rigorous physics-based simulations, you will gain valuable insights and practical knowledge. This workshop is suitable for anyone who are interested in learning about the workflow for developing Predictive Maintenance (PdM) Algorithms with MATLAB and Simulink.

In this hands-on workshop, participants will learn how to apply principles of AI (machine learning, deep learning, domain-specific preprocessing) to visual inspection workflows.

Join us for a transformative webinar on Predictive Maintenance with MATLAB and Simulink, exploring a captivating case study of a packaging machine. Discover how this innovative approach revolutionizes maintenance strategies, enhances efficiency, and leads to substantial cost savings

In this webinar, we learn of the application deployment tools and workflows that MATLAB users can employ to place their applications in the hands of their users. See how MATLAB Compiler tools allow you to create executables, host web apps and package your data in production servers.

MATLAB EXPO brings together engineers, researchers, and scientists to hear real-world examples, get hands-on demonstrations, and learn more about the latest features and capabilities of MATLAB and Simulink.

The need for advanced civil and defense systems has been brought into sharp focus. In civil, the drive for zero climate impact is driving development of advanced propulsion, autonomous systems, and urban...

This presentation considers the alternative construction of the design space based on experiment data and a grey-box model of the reactions. The models are subsequently used to optimize the production process by changing the process variables. In addition, the effect of uncertainty and variability of the parameters on the process performance is also examined with a Monte-Carlo simulation.