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Neural network method of dynamic biometrics for detecting the substitution of computer research the dynamic neural network method for biometric identification of computer users. We analyze
Two approaches to analyzing dynamic cellular networks with limited resources. Performance analysis of such networks can generally be conducted by employing queuing systems with limited
Development of unified approaches to building neural network and mathematical models based on digital data of the dynamic system. The information selected from the text data enables building of neural network
Emergence of the small-world architecture in neural networks by activity dependent growth from disconnected neurons to fully connected three-dimensional networks. For the analysis
Analysis of a semi-open queuing network with a state dependent marked Markovian arrival process, customers retrials and impatience of customer arrivals and retrials and the impatience and non-persistence of customers. Dynamics of the network
Constructing a Neural-Net Model of Network Traffic Using the Topologic Analysis of Its Time Series Complexity of building a predicting neural-net model of the time sequence of network traffic. Topological data analysis
To the analysis of the dynamic assignment of radio resources in wireless networks with a network slicing mechanismNetwork Slicing is one of the latest technologies of modern telecommunication systems. Network
A statistical model of interference in wireless networks, network-scale fading and outage probability-network density tradeoff for typical network configurations and propagation channel conditions. Network-level analysis of interference
Analysis of the mmWave mesh networks performance in dynamic blockage conditions network models that take into account the presence of dynamic locks of varying intensity and duration
The modeling of forecasting new situations in the dynamics of the economic system on the example of several financial indicators clustering was performed using topological analysis methods. Neural network models of the indicator
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