@inproceedings{fbe8541d59cb440c95bd659d2a4693ee,
title = "Application of Neural Network Based Cascade-able Transceiver Model in Serial Link Simulation",
abstract = "This paper describes the work-flow of developing black-box transceiver models for channel cascading using feedforward neural network (FNN). Compared to transistor level models, the FNN model is independent of the circuit simulator, whereas the former suffers from slow Newton-Raphson iterations. Furthermore, the generation of FNN model requires no substantial knowledge in circuit design, making it more feasible to the end-users who work in another field.",
keywords = "Transceiver modeling, cascade, channel simulation, neural network, signal integrity, time-domain",
author = "Yixuan Zhao and Thong Nguyen and Schutt-Aine, {Jose E.}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 26th IEEE Workshop on Signal and Power Integrity, SPI 2022 ; Conference date: 22-05-2022 Through 25-05-2022",
year = "2022",
doi = "10.1109/SPI54345.2022.9874932",
language = "English (US)",
series = "26th IEEE Workshop on Signal and Power Integrity, SPI 2022 - Conference Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "26th IEEE Workshop on Signal and Power Integrity, SPI 2022 - Conference Proceedings",
address = "United States",
}