In this article, we cover the fundamentals of neural networks and Bayesian learning with a
focus on signal and power integrity problems arising in packaging. Rather than only focus …

Placing ground vias plays a crucial role in mitigating electromagnetic radiation from printed
circuit board (PCB) edges. Stitching dense ground vias along PCB edges is not always …

This article demonstrates a deep learning (DL)-based methodology for the rapid simulation
of planar microwave circuits based on their layouts. We train convolutional neural networks …

With the tremendous growth of the semiconductor industry, compute power and memory
have become cheap and accessible. One interesting outcome of this growth has been the …

Neural networks (NNs) are quite attractive in creating surrogate models for many signal
integrity (SI) applications. NN-based surrogate models offer the benefits of reducing the …

With the rapid development of electronic technology, signal integrity (SI) analysis of high-
speed circuit channels has become a challenging task. As SI designs become increasingly …

Ground vias are often used as an essential shielding structure in System-in-Package (SiP) to
suppress electromagnetic leakage. In this paper, a new method based on Convolutional …

The measurement of radiated emission (RE) in an anechoic chamber becomes very
challenging at high frequencies, up to 60 GHz, because the scanning plane of the receiver is …

A machine learning model that predicts automotive radiated emissions under CISPR25
conditions from near-field noise is developed as a neural network. The model demonstrates …

Machine learning (ML) is one of today's most studied subjects in almost every research area.
It provides interesting mathematical tools that could inspire us to rethink about the EMC/SI/PI …