A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
In this paper, we propose and explain a neural circuitry based on single electron transistors 'SET' which can be used in classification and recognition. We implement, after that, a Winner-Take-All 'WTA' neural network with lateral inhibition architecture. The original idea of this work is reflected, first, in the proposed new single electron memory 'SEM' design by hybridising two promising Single Electron Memory 'SEM' and the MTJ/Ring memory and second, in modeling and simulation results ofdoaj:7cd98724a15846c58044d2ac79eb12b7 fatcat:c5lwfgfblfb7dieod43ks7ntyu