Methodology to Predict Random Telegraph Noise Induced Threshold Voltage Shift Using Machine Learning

We suggest the methodology to predict the distribution of threshold voltage $(V_{t})$ shift caused by random telegraph noise (RTN). Poly-silicon channels were randomized with a single trap and the neural network was modeled to predict RTN trap-induced $(V_{t})$ fluctuation in 3D NAND Flash Memory. 3D Technology Computer-Aided Design (TCAD) simulations were performed in a unit cell to calculate the Vt shift in a 3D vertical channel. Finally, we extract the distribution of $\mathbf{V}_{\mathbf{t}}$ fluctuation using machine learning.