Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Conference Proceedings |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 121-126 |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 9781479966912 |
| Publikationsstatus | Veröffentlicht - 14 Nov. 2014 |
| Veranstaltung | 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Colchester, Großbritannien / Vereinigtes Königreich Dauer: 25 Sept. 2014 → 26 Sept. 2014 |
Publikationsreihe
| Name | 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Conference Proceedings |
|---|
Abstract
Machine learning algorithms have recently been used successfully to generate behavioral models of analog circuits. We take this approach one step further and include parameter variations directly into models using specialized interval arithmetics. We developed a new support vector machine algorithm which estimates functions with interval-valued parameters. We applied this approach to modeling non-linear, static transfer functions of analog circuits with parameter variations and successfully simulated these models using a custom-built simulator.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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- BibTex
- RIS
2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. S. 121-126 6958566 (2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Conference Proceedings).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Variation-aware behavioral models of analog circuits using support vector machines with interval parameters
AU - Krause, Anna
AU - Olbrich, Markus
AU - Barke, Erich
N1 - Publisher Copyright: © 2014 IEEE. Copyright: Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014/11/14
Y1 - 2014/11/14
N2 - Machine learning algorithms have recently been used successfully to generate behavioral models of analog circuits. We take this approach one step further and include parameter variations directly into models using specialized interval arithmetics. We developed a new support vector machine algorithm which estimates functions with interval-valued parameters. We applied this approach to modeling non-linear, static transfer functions of analog circuits with parameter variations and successfully simulated these models using a custom-built simulator.
AB - Machine learning algorithms have recently been used successfully to generate behavioral models of analog circuits. We take this approach one step further and include parameter variations directly into models using specialized interval arithmetics. We developed a new support vector machine algorithm which estimates functions with interval-valued parameters. We applied this approach to modeling non-linear, static transfer functions of analog circuits with parameter variations and successfully simulated these models using a custom-built simulator.
UR - http://www.scopus.com/inward/record.url?scp=84915749650&partnerID=8YFLogxK
U2 - 10.1109/CEEC.2014.6958566
DO - 10.1109/CEEC.2014.6958566
M3 - Conference contribution
AN - SCOPUS:84915749650
T3 - 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Conference Proceedings
SP - 121
EP - 126
BT - 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 6th Computer Science and Electronic Engineering Conference, CEEC 2014
Y2 - 25 September 2014 through 26 September 2014
ER -