Name
Abstract | ||
|---|---|---|
Theoretical analyses as well as case studies have established that behavioral models based on a recurrent neural network (RNN) are suitable for transient modeling of nonlinear circuits. After training, an RNN model can be implemented in Verilog-A and evaluated by a SPICE-type circuit simulator. This paper describes hurdles that have prevented wide-scale adoption of the RNN as an IP-obscuring behav... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MLCAD52597.2021.9531153 | 2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD (MLCAD) |
Keywords | DocType | ISBN |
transient models,recurrent neural network,circuit simulation,neural ODE | Conference | 978-1-6654-3166-8 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jie Xiong | 1 | 0 | 0.34 |
| Alan S. Yang | 2 | 0 | 0.34 |
| Maxim Raginsky | 3 | 771 | 60.65 |
| Elyse Rosenbaum | 4 | 61 | 21.99 |