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