140 search results - page 2 / 28 » Perspectives and challenges for recurrent neural network tra... |
ICANN
2009
Springer
14 years 8 days 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...
IAJIT
2010
13 years 6 months ago
2010
: 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...
ICANN
2001
Springer
14 years 4 days ago
2001
Springer
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
This paper shows that a novel hybrid algorithm, Breeding Swarms, performs equal to, or better than, Genetic Algorithms and Particle Swarm Optimizers when training recurrent neural...
IJON
2007
13 years 7 months ago
2007
To predict the 100 missing values from a time series of 5000 data points, given for the IJCNN 2004 time series prediction competition, recurrent neural networks (RNNs) are trained...