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.
This webinar explores how AI‑based virtual sensors can be used to estimate signals that are difficult or costly to measure, such as battery state of charge (SOC) in Battery Management Systems. Using a practical example, the session demonstrates how AI models can be integrated into system‑level design and validated against performance, resource, and deployment constraints.
The workflow shows how to design, verify, compress, and deploy AI‑based virtual sensors to embedded processors within a single environment.
You will learn how to:
Integrate AI models into Simulink® for system‑level simulation and verification
Apply formal verification to assess neural network behavior
Optimize models for memory footprint and execution speed
Generate and profile library‑free C code for embedded deployment
Evaluate design tradeoffs across accuracy, performance, and deployment targets
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