Stochastic template in cellular nonlinear networks modeling memristor induced synaptic noise

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review



Noise is one of the most challenging aspects of cellular nonlinear networks adversely affecting their functionality. Existing techniques to addressing the issues posed by noise are based on well-understood noise removal methods that have reached technical maturity and further have the disadvantage of limited success rates. A deeper understanding and modeling of noise dynamics and its origins are required for the efficient identification and resolution of problems in different network applications. The Stochastic template concept in this article can be beneficial in understanding and modeling noise dynamics in cellular nonlinear networks, which is critical for addressing challenges in network applications. In this paper, memristors functioning as synapses introduce noise into networks, and we conduct an initial investigation of a noisy network performing edge detection.


Original languageEnglish
Title of host publicationProceedings of the 18th ACM International Symposium on Nanoscale Architectures, NANOARCH 2023
PublisherAssociation for Computing Machinery
ISBN (electronic)9798400703256
Publication statusPublished - 18 Dec 2023

Publication series

SeriesACM International Conference Proceeding Series


Title18th ACM International Symposium on Nanoscale Architectures
Abbreviated titleNANOARCH 2023
Conference number18
Duration18 - 20 December 2023
LocationTechnische Universität Dresden

External IDs

ORCID /0000-0002-1236-1300/work/154191445
ORCID /0000-0001-7436-0103/work/154191787
ORCID /0000-0002-6200-4707/work/154192566



  • Cellular Nonlinear Networks, Memristive Synapses, Noise