Abstract
Recent success of recurrent neural network (RNN) in modeling time sequence has drawn a lot of attentions across multiple fields. Prior works have shown that RNN modeling can be suitable and even powerful for macro-modeling in circuit simulation. In this work, we propose using RNN for high-speed channel simulation in the time domain, which can handle the nonlinear behaviors of the IO buffers. The numerical example has demonstrated the capability and the accuracy of the proposed approach. Through the numerical example, we investigate the multiple well-known RNN structures on their capability of accurate transient channel simulation. We also examine the tunable parameters in the RNN model such as the optimization method in dealing with nonlinearities.
Original language | English (US) |
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Title of host publication | EPEPS 2018 - IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 303-305 |
Number of pages | 3 |
ISBN (Electronic) | 9781538693032 |
DOIs | |
State | Published - Nov 13 2018 |
Externally published | Yes |
Event | 27th IEEE Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2018 - San Jose, United States Duration: Oct 14 2018 → Oct 17 2018 |
Publication series
Name | EPEPS 2018 - IEEE 27th Conference on Electrical Performance of Electronic Packaging and Systems |
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Conference
Conference | 27th IEEE Conference on Electrical Performance of Electronic Packaging and Systems, EPEPS 2018 |
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Country/Territory | United States |
City | San Jose |
Period | 10/14/18 → 10/17/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.