Overview: We have developed an accurate fault modeling tool to capture variation-induced faults in Networks-on-Chip (NoCs). The core of our fault model has circuit-level accuracy, while its ...

AWARE uses waveform signatures to detect and classify early-stage grid faults, enabling proactive intervention. The system combines physics-based models with AI/ML to interpret subtle electrical ...

A different set of fault models and testing techniques is required for memory blocks vs. logic. MBIST algorithms that are used to detect faults inside memory are based upon these fault models. This ...

A team of scientists in the United States has combined both spatial and temporal attention mechanisms to develop a new approach for PV inverter fault detection. Training the new method on a dataset ...