Neural Circuitry Based on Single Electron Transistors and Single Electron Memories
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,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IFSA Publishing, S.L.
2014-05-01
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| Series: | Sensors & Transducers |
| Subjects: | |
| Online Access: | http://www.sensorsportal.com/HTML/DIGEST/may_2014/Special_issue/P_SI_484.pdf |
| Summary: | 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 of neural memory based on SET. We prove the charge storage in quantum dot in two types of memories.
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| ISSN: | 2306-8515 1726-5479 |