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.
In this paper, we proposed an improved discrete Hopfield neural network (DHNN) for Max-Cut problems. By introducing a nonlinear self-feedback term to the motion equation of the DHNN, the DHNN can escape from local minima and therefore get better solutions.
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To convert 110 lbs to kg multiply the mass in pounds by 0.45359237. The 110 lbs in kg formula is [kg] = 110 * 0.45359237. Thus, for 110 pounds in kilogram we get 49.8951607 kg.
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