In a Hopfield neural network, every neuron is connected with other neurons directly. In this network, a neuron is either ON or OFF. The state of the neurons can change by receiving inputs from other neurons. We generally use Hopfield networks (HNs) to store patterns and memories. When we train a neural network on a set of patterns, it can then recognize the pattern even if it is somewhat distorted or incomplete.