The uplearning of the Hopfield neural network: the search for a global minimum of a functional and the model of rapid eye movement

The traveling salesman problem is solved using the Hopfield neural network model. The solution comes to the energy minimization of the neural network for the purpose of finding the global minimum of an appropriate functional. The procedure “Uplearning” is introduced. In addition, local minima become deeper rising one's accessibility in this process. In this case, just the global minimum survives frequently. The results are represented which help to guess that the Uplearning increases the probability to find the global minimum in contrast to the Unlearning which was introduced by Hopfield in 1983.