Neural Network Based on SET Inverter Structures: Neuro-Inspired Memory

Bilel Hafsi^1,2*, Rabii Elmissaoui³, Adel Kalboussi¹

¹IEMN Laboratory, University of Lille1, Avenue Poincaré, 59652 Villeneuve d’Ascq Cedex, France.
²Microelectronics and Instrumentation Laboratory, Faculty of Sciences of Monastir, University of Monastir, Monastir, Tunisia.
³Research Unit on Study of Industrial Systems and Renewable Energies, National Engineering School of Monastir, Monastir, Tunisia.

DOI: 10.4236/wjnse.2014.44017                

Abstract

This paper presents a basic block for building large-scale single-electron neural networks. This macro block is completely composed of SET inverter circuits. We present and discuss the basic parts of this device. The full design and simulation results were done using MATLAB and SIMON, which are a single-electron tunnel device and circuit simulator based on a Monte Carlo method. Special measures had to be taken in order to simulate this circuit correctly in SIMON and compare results with those of SPICE simulation done before. Moreover, we study part of the network as a memory cell with the idea of combining the extremely low-power properties of the SET and the compact design.

Keywords

Single-Electron, Neuron, Synapse, Inverter, Neural Network, Single-Electron Memory, Perceptron, MATLAB, SIMON

Conflicts of Interest

The authors declare no conflicts of interest.

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