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In this study, we investigate and implemdhnnent a discrete Hopfield neural network (DHNN) using SFQ circuits. A DHNN is a binary neural network with less information than a standard full precision neural network; it also provides a higher processing speed.

DHNN is a simple structure with no hidden layer and binary input/output which leads to lower complexity compared to other networks. Satisfiability as a neuron representation is considered a suitable logical structure due to its simple constructiodhnnn.

The main highlight of DHNN is the present of content associative memory (CAM) whereby it is used to store the pattern of the problem and it consists of interconnected neurons with no hidden layer which act as the potential characteristics for solving optimization problems (Guo, et al., 2022).

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