Compact Modeling of Single Electron Memory Based on Perceptron Designs
Boubaker A, Nasri A, Hafsi B* and Kalboussi A
Faculty of Science of Monastir, Microelectronics and Instrumentation Laboratory, Avenue de l’Environnement-5019, Monastir, Tunisia
- *Corresponding Author:
- Hafsi B
Faculty of Science of Monastir
Microelectronics and Instrumentation Laboratory
Avenue de l’Environnement-5019, Monastir, Tunisia
Tel: 216 98 226 408
E-mail: [email protected]
Received Date: July 25, 2015; Accepted Date: August 05, 2015; Published Date: August 15, 2015
Citation: Boubaker A, Nasri A, Hafsi B, Kalboussi A (2015) Compact Modeling of Single Electron Memory Based on Perceptron Designs. J Material Sci Eng 4: 187. doi:10.4172/2169-0022.1000187
Copyright: © 2015 Boubaker A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
In this work, we present a Single electron random access memories based on perceptron designs used as the basic artificial bio-inspired neural processing element. The operation principles are described and illustrated for the first time by simulations results. Combining the Monte Carlo method with a direct solution of the stationary master equation, we use SIMON simulator and MATLAB for training process. The main goal of this work is to build a multilayer neural network used in recognition and classification using single electron devices. We further provide a write/Erase/ Read states chronogram to provide the key element of our work which is the charge stored in output neuron’s quantum dots.