We consider the problem of routing in intermittently connected networks. In such networks there is no guarantee that a fully connected path between source and destination exist at...
: This paper describes the development of neural network models for noise reduction. The networks used to enhance the performance of modeling captured signals by reducing the effec...
The second smallest eigenvalue of the Laplacian matrix, also known as the algebraic connectivity, plays a special role for the robustness of complex networks since it measures the ...
The features of neural networks using for increasing of an accuracy of physical quantity measurement are considered by prediction of sensor drift. The technique of data volume incr...
In this note we present and discuss results of experiments comparing the performance of six neural network architectures (back propagation, recurrent network with dampened feedbac...
Marcin Paprzycki, Rick Niess, Jason Thomas, Lenny ...