AI for Simulink Users

Deep learning and machine learning techniques have demonstrated the ability to solve complex problems that traditional methods can’t adequately model, such as detecting objects in an image or accurately predicting battery state-of-charge based on current and voltage measurements.  While these capabilities by themselves are remarkable, the AI model  typically represents only a small piece of a larger system. For example, embedded software for self-driving car may have different adaptive cruise control, lane keep control, sensor fusion, LIDAR logic, and many other components in addition to deep learning-based computer vision. How do you integrate, implement, and test all these different components together while minimizing expensive testing with actual hardware and the vehicle?

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