Image Recognition Task Based on Decoupled Single-Electron Hamming Networks

This paper presents a black and white image recogniton task implemented using a decoupled single-electron (SET) Hamming neural network. For the first time, more than 18000 single-electron transistors are used in such a task. This network allows a more practical hardware implementation. Simulation results for various temperatures are presented. A vector clustering task is simulated using SIMON. Robustness against random offset charges, as well as dynamic behavior are evaluated.