On the implementation of cellular wave computing methods by hardware learning
Publikation: Beitrag in Fachzeitschrift › Konferenzartikel › Beigetragen › Begutachtung
Beitragende
Abstract
Adaptive signal processing on Cellular Nonlinear Networks (CNN) based electronic devices is an exciting challenge, which needs a fast and robust parameter adaptation. In this contribution implementations and the analysis of optimisation algorithms will be proposed and discussed using the EyeRIS™hardware system with an embedded ACE16kv2 focal plane processor having 128 × 128 cells. The parameter training performance will be analysed in detail.
Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 4253292 |
| Seiten (von - bis) | 2930-2933 |
| Seitenumfang | 4 |
| Fachzeitschrift | Proceedings - IEEE International Symposium on Circuits and Systems |
| Publikationsstatus | Veröffentlicht - 2007 |
| Peer-Review-Status | Ja |
Konferenz
| Titel | 2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007 |
|---|---|
| Dauer | 27 - 30 Mai 2007 |
| Stadt | New Orleans, LA |
| Land | USA/Vereinigte Staaten |
Externe IDs
| ORCID | /0000-0001-7436-0103/work/173513961 |
|---|
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Cellular nonlinear networks, EyeRIS visual system, Intelligent sensors, Optimisation algorithm