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ICANN
2009
Springer
15 years 4 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
ESANN
2003
15 years 1 months ago
Self-organizing maps and functional networks for local dynamic modeling
The paper presents a method for times series prediction using a local dynamic modeling based on a three step process. In the first step the input data is embedded in a reconstruct...
Noelia Sánchez-Maroño, Oscar Fontenl...
ICIC
2005
Springer
15 years 5 months ago
A Nonlinear Adaptive Predictive Control Algorithm Based on OFS Model
Firstly, a method is introduced which uses Volterra series deploying technique to construct a nonlinear model based on OFS model. Then an improved novel incremental mode multiple s...
Haitao Zhang, Zonghai Chen, Ming Li, Wei Xiang, Ti...
IJCNN
2007
IEEE
15 years 6 months ago
Neural Network Ensembles for Time Series Prediction
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
Dymitr Ruta, Bogdan Gabrys
ICNC
2005
Springer
15 years 5 months ago
A Time-Series Decomposed Model of Network Traffic
: Traffic behavior in a large-scale network can be viewed as a complicated non-linear system, so it is very difficult to describe the long-term network traffic behavior in a large-...
Guang Cheng, Jian Gong, Wei Ding 0001