Abstract: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.
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