The report is devoted to a possibility of a control of each Hopfield’s neuron as an elementary unit of the neural network with variable signal conductivity used for transport scheduling tasks. It is set that direct control of the neuron is impossible in terms of initial data available for initializing the neural network. Also the result of some control algorithms based on statistical computations and signals dynamic is described below.

The article sets and solves the task to control an error of the artificial neural network with variable signal conductivity.

The article focuses on a new extent to synthesize a control strategy of learning of a special artificial neural network with variable signal conductivity and on features of neural networks with variable signal conductivity. The purpose of the research is to create a new control strategy based on analysis of the neural network error signal. Also the article contains an approach how to compute the control strategy. The main result is contained in the necessity to realize the control strategy on the basis of preliminary training of the neural network with specific techniques. Authors also suggest a technique of computing the crucial trajectory of the network's error decreasing. The trajectory may be computed using signal processing methods.