@inproceedings{868a153709a348f4abf442c246a0151e,
title = "Verilog-A compatible recurrent neural network model for transient circuit simulation",
abstract = "This paper presents a method for data-driven behavioral modeling of electronic circuits using recurrent neural networks (RNNs). The RNN structure is adapted based on known characteristics of the system being modeled. The discrete-time RNN is transformed to a continuous-time model and then implemented in Verilog-A for compatibility with general-purpose circuit simulators.",
keywords = "Behavioral models, Circuit simulation, Recurrent neural network, Verilog-A",
author = "Zaichen Chen and Maxim Raginsky and Elyse Rosenbaum",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 26th IEEE Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2017 ; Conference date: 15-10-2017 Through 18-10-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/EPEPS.2017.8329743",
language = "English (US)",
series = "2017 IEEE 26th Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--3",
booktitle = "2017 IEEE 26th Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2017",
address = "United States",
}