Synchronization properties of a bio-inspired neural network

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Contributors

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

Original languageEnglish
Title of host publicationIEEE-NANO 2015 - 15th International Conference on Nanotechnology
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages621-624
Number of pages4
ISBN (electronic)9781467381550
Publication statusPublished - 2015
Peer-reviewedYes

Conference

Title15th IEEE International Conference on Nanotechnology, IEEE-NANO 2015
Duration27 - 30 July 2015
CityRome
CountryItaly

External IDs

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

Keywords

Keywords

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