AI with Model-Based Design: Virtual Sensor Modeling
This webinar presents a workflow offering end-to-end solutions for designing, training, validating and verifying, compressing, and deploying AI-based virtual sensor models to embedded processors within a single environment. Highlights Integrate AI models into Simulink for system-level simulation, verification, and simulation-based testing Apply formal verification techniques to assert neural network behavior Compress the AI model for memory footprint reduction and execution s
A new webinar introduces a comprehensive workflow for developing AI-powered virtual sensor models. This integrated approach allows for the design, training, validation, compression, and deployment of these models onto embedded processors within a unified environment. Key features include integrating AI models into Simulink for system-level simulation and testing, applying formal verification to ensure neural network reliability, and compressing models to optimize memory usage and processing speed. The process also involves generating C code without external libraries and conducting processor-in-the-loop tests to assess performance and design choices.
This workflow enables engineers to efficiently create and deploy sophisticated AI virtual sensors, potentially leading to more intelligent and responsive embedded systems.
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