Name
Abstract | ||
|---|---|---|
Artificial Neural Networks (ANN) are gaining attention in the semiconductor modeling area, as alternative to physical modeling of high speed devices. A fundamental issue when including ANN's in a circuit simulator is how to manage the time dependency. One elegant solution recently proposed is the Dynamic Neural Network concept, where neurons are instances of differential equations. In this work the dynamic approach and further variations has been compared with classical static ANN, applied to the modeling of high performance bipolar junction transistor. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1007/3-540-44668-0_97 | ICANN |
Keywords | Field | DocType |
dynamic approach,differential equation,circuit simulator,circuit simulators,artificial neural networks,dynamic neural network concept,high speed device,semiconductor modeling area,high performance bipolar junction,physical modeling,classical static ann,artificial neural network,neural network,bipolar junction transistor,physical model | Differential equation,Computer science,Computer Aided Design,Electronic engineering,Bipolar junction transistor,Artificial intelligence,Electronic circuit simulation,Artificial neural network,Dynamic neural network,Distributed computing | Conference |
Volume | ISSN | ISBN |
2130 | 0302-9743 | 3-540-42486-5 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessio Plebe | 1 | 59 | 11.23 |
| Marcello A. Anile | 2 | 7 | 1.86 |
| Salvatore Rinaudo | 3 | 38 | 11.36 |