A New Method of Automatic Extraction of RTN and OMI-friendly implementation

In this paper, based on the non-Gaussian nature of RTN, we propose a method for the fully automated random telegraph noise (RTN) analysis, including the detection/identification of the number of traps and extraction of each trap's parameter, which makes the analysis of complex RTN more effective. By improving the efficiency of the hidden Markov model (HMM) algorithm through an adaptive model, over 10 times faster performance has been achieved compared to the conventional method. Finally, we incorporate the compact model of RTN into the circuit simulator by utilizing the Open Model Interface (OMI). This integration allows for better evaluation on the impact of RTN through circuit-level simulations, facilitating the resilient and robust future circuit designs.