Name
Title | ||
|---|---|---|
Improvement of ANNs Performance to Generate Fitting Surfaces for Analog CMOS Circuits |
Abstract | ||
|---|---|---|
One of the typical applications of neural networks is based on their ability to generate fitting surfaces. However, for certain problems, error specifications are very restrictive, and so, the performance of these networks must be improved. This is the case of analog CMOS circuits, where models created must provide an accuracy which some times is difficult to achieve using classical techniques. In this paper we describe a modelling method for such circuits based on the combination of classical neural networks and electromagnetic techniques. This method improves the precision of the fitting surface generated by the neural network and keeps the training time within acceptable limits. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-73055-2_3 | international work-conference on the interplay between natural and artificial computation |
Keywords | Field | DocType |
classical neural network,neural network,Analog CMOS Circuits,certain problem,fitting surface,Fitting Surfaces,modelling method,error specification,classical technique,acceptable limit,ANNs Performance,electromagnetic technique,analog CMOS circuit | Computer science,CMOS,Artificial intelligence,Electronic circuit,Artificial neural network,Machine learning | Conference |
Volume | ISSN | Citations |
4528 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Ángel Díaz-Madrid | 1 | 1 | 2.10 |
| Pedro Monsalve-Campillo | 2 | 0 | 0.34 |
| Juan Hinojosa | 3 | 1 | 2.09 |
| María Victoria Rodellar Biarge | 4 | 44 | 13.67 |
| Ginés Doménech-Asensi | 5 | 34 | 10.98 |