Toward nanoelectronic cellular neural networks

C. Gerousis, Stephen Goodnick, W. Porod

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


We investigate the use of nanoelectronic structures in cellular non-linear network (CNN) architectures, for potential application in future high-density and low-power CMOS-nanodevice hybrid circuits. We first investigate compact models for simulation of single-electron tunnelling (SET) transistors appropriate for use in coupled SET-CMOS circuits. We then discuss simple CNN linear architectures using a SET inverter topology as the basis for the non-linear transfer characteristic of individual cells. This basic SET CNN cell acts as a summing node, which is capacitively coupled to the inputs and outputs of nearest neighbour cells. Monte Carlo simulation results are then used to show CNN-like behaviour in attempting to realize different functionality such as a connected component detector and shadowing.

Original languageEnglish (US)
Pages (from-to)523-535
Number of pages13
JournalInternational Journal of Circuit Theory and Applications
Issue number6
StatePublished - Nov 1 2000


  • Cellular non-linear networks
  • Nanoelectronics
  • Single-electron devices

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


Dive into the research topics of 'Toward nanoelectronic cellular neural networks'. Together they form a unique fingerprint.

Cite this