dhnn|Design of Discrete Hopfield Neural Network Using a Single Flux。,what does egirl stand for

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 construction.

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).

DHNN is a minimalistic and Numpy based implementation of the Discrete Hopfield Network. DHNN can learn (memorize) patterns and remember (recover) the patterns when the network feeds those with noises.

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