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PROJECT TITLE :

Automated Transient Input Stimuli Generation for Analog Circuits

ABSTRACT:

We gift an automatic directed random input stimulus generation algorithm with high coverage for nonlinear analog circuits. Our methodology is ready to come up with input stimuli to meet two types of objectives: one) to succeed in user-defined goal regions and a couple of) increased coverage of state house. The principal benefit of our approach is that it can give directed input stimulus generation, vs the randomly generated input stimulus by Monte Carlo-based mostly strategies. The methodology introduces multiobjective rapidly-exploring random trees (MORRTs), that add a bias and a feedback loop to the quality rapidly-exploring random trees algorithm. The biasing is provided by a statistical inference algorithm. Simultaneous biasing toward goal regions and coverage is attainable in MORRT to a user-defined extent. Our methodology generates many input stimuli that are concentrated in the goals or relevant operating regions, while providing high coverage of the state area. We demonstrate the efficiency and scalability of our approach on high-dimensional analog case studies.


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