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.
DHNN™ exists to transform our surroundings and ourselves through design, empathy and a restless quest for quality.
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 wdhnnith no hidden layer which act as the potential characteristics for solving optimization problems (Guo, et al., 2022).
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