The article is devoted to an artificial neural network that increases image resolution. According to the meaning of the article, two parts can be distinguished. The first part of the article discusses the process of designing an artificial neural network using DAGNet technology, during which its main parameters and structure are described. The second part is devoted to assessing the quality of functioning of the developed artificial neural network. To evaluate the performance of ANNs a comparative analysis with the bicubic interpolation method was used.

This article discusses an approach to monitoring optimization in telecommunication networks with packet routing. Mathematical model of data networking with accounting for monitoring traffic structure is described, optimization task is determined. Main attention is paid to model development on the basis of queueing theory in order to generation of reserve capacity in system. The main concept is that comparatively simple structure of monitoring network is imposed on physical structure of telecommunication network. The modeling is aimed at selection of optimum parameters of monitoring system, solution techniques for similar task are proposed. The obtained optimization task is sufficiently complicated, subsequent attempts should be aimed at searching for conditions which would enable introduction of some constraints in order to simplify its solution without noticeable loss of the model adequacy. This is especially important for asynchronous task of monitoring, it should be based on selection of the most acceptable type of objective function (linear or quadratic).