Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Abstract— Within assembly lines, wheel assembly to continuously conveyed car bodies is still executed by human workers using a device that compensates the weight of the wheel. Th...
Friedrich Lange, Jochen Werner, Johannes Scharrer,...
This pape? presents a novel approach to dynamic transmission bandwidth allocation for transport of real-time variable-bit-rate video in ATM networks. Describe video traffic in the...