5 search results - page 1 / 1 » An investigation of the state formation and transition limit... |
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
2008
13 years 6 months ago
2008
Frequently, sequences of state transitions are triggered by specific signals. Learning these triggered sequences with recurrent neural networks implies storing them as different at...
ICANN
2009
Springer
13 years 9 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...
IJCNN
2006
IEEE
13 years 11 months ago
2006
IEEE
—This paper investigates the application of a new kind of recurrent neural network called Echo State Networks (ESNs) for the problem of measuring the actual amount of harmonic cu...
NIPS
2004
13 years 6 months ago
2004
The formation of disulphide bridges among cysteines is an important feature of protein structures. Here we develop new methods for the prediction of disulphide bond connectivity. ...