Synchronization properties of a bio-inspired neural network
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
Certain two-terminal devices exhibiting the finger-prints of memristive behavior offer the possibility to mimic the dynamics of biological synapses with a higher level of accuracy as compared to their current electronic realizations. It has been recently shown that neural networks with memristive synapses may exhibit distinct synchronization properties over equivalent diffusively-coupled systems. Applying concepts from the contraction mapping theory, this paper derives analytical conditions for the emergence of synchronization in a memristive neural network of Hindmarsh-Rose neurons. The results reveal the crucial impact the initial memristor state has on the development of synchronous oscillations in the network.
Details
| Originalsprache | Englisch |
|---|---|
| Titel | IEEE-NANO 2015 - 15th International Conference on Nanotechnology |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers (IEEE) |
| Seiten | 621-624 |
| Seitenumfang | 4 |
| ISBN (elektronisch) | 9781467381550 |
| Publikationsstatus | Veröffentlicht - 2015 |
| Peer-Review-Status | Ja |
Konferenz
| Titel | 15th IEEE International Conference on Nanotechnology, IEEE-NANO 2015 |
|---|---|
| Dauer | 27 - 30 Juli 2015 |
| Stadt | Rome |
| Land | Italien |
Externe IDs
| ORCID | /0000-0001-7436-0103/work/172566282 |
|---|
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Contraction Mapping Theory, Hindmarsh-Rose neuron, Memristor, Oscillatory networks, Synchronization