Synchronization properties of a bio-inspired neural network

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

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

OriginalspracheEnglisch
TitelIEEE-NANO 2015 - 15th International Conference on Nanotechnology
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers (IEEE)
Seiten621-624
Seitenumfang4
ISBN (elektronisch)9781467381550
PublikationsstatusVeröffentlicht - 2015
Peer-Review-StatusJa

Konferenz

Titel15th IEEE International Conference on Nanotechnology, IEEE-NANO 2015
Dauer27 - 30 Juli 2015
StadtRome
LandItalien

Externe IDs

ORCID /0000-0001-7436-0103/work/172566282

Schlagworte

Schlagwörter

  • Contraction Mapping Theory, Hindmarsh-Rose neuron, Memristor, Oscillatory networks, Synchronization