139 search results - page 2 / 28 » Multi-step-ahead prediction using dynamic recurrent neural n... |
ACSC
2008
IEEE
13 years 7 months ago
2008
IEEE
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...
ESANN
2003
13 years 6 months ago
2003
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
ICANN
2009
Springer
13 years 10 months ago
2009
Springer
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
AI50
2006
13 years 9 months ago
2006
This case study demonstrates how the synthesis and the analysis of minimal recurrent neural robot control provide insights into the exploration of embodiment. By using structural e...
NPL
2011
12 years 8 months ago
2011
The accuracy of a model to forecast a time series diminishes as the prediction horizon increases, in particular when the prediction is carried out recursively. Such decay is faster...