Join this webinar to learn how to develop virtual sensor models using feedforward neural networks, LSTMs, decision trees, and other AI techniques. Using the example of BMS SOC estimation, you will learn how to integrate AI models into Model-Based Design, so you are then able to test your design using simulation and implement it on an NXP S32K3xx board using automatic code generation. Discover how to evaluate and manage AI tradeoffs that span from model accuracy to deployment efficiency.
Topics include:
- Designing and training machine learning components with Statistics and Machine Learning Toolbox
- Designing and training deep learning components with Deep Learning Toolbox
- Importing trained TensorFlow models into MATLAB
- Integrating machine learning and deep learning models into Simulink for system-level simulation
- Generating library-free C code and performing PIL tests
Speaker:
Lucas García, Senior Product Manager for Deep Learning at MathWorks
Date and time:
17th August – 14:00 – 15:00 (UTC)
