Efficient Estimation of PSIJ via Jitter Transfer Function and Knowledge-based Neural Networks

In this paper, an efficient method for analysis of power supply induced jitter (PSIJ) is presented. In the proposed approach, the noise spectrum for an arbitrary noise is generated via Fourier series and the knowledge-based neural network (KBNN) is generated to accurately predict the response of PSIJ transfer function (PSIJTF) using the training data extracted from two types of models, analytical closed-form expressions as well as computationally expensive circuit simulator. Employing KBNN based transfer function model with the noise spectrum gives reasonably accurate estimation of PSIJ for multiple input noises. A case study with 32nm CMOS technology is presented to demonstrate the validity of the proposed model compared to a circuit simulator.