Abstract
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 on mathematical formulations, we explain the important concepts and the intuition behind them, thereby demystifying the use of machine learning for these problems. We also share some of the recent developments in this area along with future research directions in the context of packaging. Links to open-source downloadable software for some of the methods discussed are also provided.
Original language | English (US) |
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Article number | 9149655 |
Pages (from-to) | 1276-1295 |
Number of pages | 20 |
Journal | IEEE Transactions on Components, Packaging and Manufacturing Technology |
Volume | 10 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2020 |
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering