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» An EM Based Training Algorithm for Recurrent Neural Networks
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IAJIT
2010
117views more  IAJIT 2010»
13 years 3 months ago
Development of Neural Networks for Noise Reduction
: 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...
Lubna Badri
IJCNN
2006
IEEE
13 years 11 months ago
Recurrent Neural Network Based Predictions of Elephant Migration in a South African Game Reserve
Abstract— A large portion of South Africa’s elephant population can be found on small wildlife reserves. When confined to enclosed reserves the elephant densities are much hig...
Parviz Palangpour, Ganesh K. Venayagamoorthy, Kevi...
GECCO
2005
Springer
196views Optimization» more  GECCO 2005»
13 years 10 months ago
Breeding swarms: a new approach to recurrent neural network training
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...
Matthew Settles, Paul Nathan, Terence Soule
TNN
1998
92views more  TNN 1998»
13 years 4 months ago
Inductive inference from noisy examples using the hybrid finite state filter
—Recurrent neural networks processing symbolic strings can be regarded as adaptive neural parsers. Given a set of positive and negative examples, picked up from a given language,...
Marco Gori, Marco Maggini, Enrico Martinelli, Giov...
ICANN
2001
Springer
13 years 9 months ago
Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks
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...
Juan Antonio Pérez-Ortiz, Jorge Calera-Rubi...