Synchronization properties of a bio-inspired neural network
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
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 language | English |
---|---|
Title of host publication | IEEE-NANO 2015 - 15th International Conference on Nanotechnology |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 621-624 |
Number of pages | 4 |
ISBN (electronic) | 9781467381550 |
Publication status | Published - 2015 |
Peer-reviewed | Yes |
Conference
Title | 15th IEEE International Conference on Nanotechnology, IEEE-NANO 2015 |
---|---|
Duration | 27 - 30 July 2015 |
City | Rome |
Country | Italy |
External IDs
ORCID | /0000-0001-7436-0103/work/172566282 |
---|
Keywords
ASJC Scopus subject areas
Keywords
- Contraction Mapping Theory, Hindmarsh-Rose neuron, Memristor, Oscillatory networks, Synchronization