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ICANN
2009
Springer
15 years 2 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
IJCNN
2000
IEEE
15 years 2 months ago
Neuro-Wavelet Parametric Modeling
This w orkshows how to train the activation function in neuro-wavelet parametric modeling and how this improves performance in a number of modeling, classi cation and forecasting.
Valentina Colla, Mirko Sgarbi, Leonardo Maria Reyn...
SIGMETRICS
2012
ACM
248views Hardware» more  SIGMETRICS 2012»
13 years 9 days ago
Pricing cloud bandwidth reservations under demand uncertainty
In a public cloud, bandwidth is traditionally priced in a pay-asyou-go model. Reflecting the recent trend of augmenting cloud computing with bandwidth guarantees, we consider a n...
Di Niu, Chen Feng, Baochun Li
ESANN
2007
14 years 11 months ago
Causality analysis of LFPs in micro-electrode arrays based on mutual information
Since perceptual and motor processes in the brain are the result of interactions between neurons, layers and areas, a lot of attention has been directed towards the development of...
Nikolay V. Manyakov, Marc M. Van Hulle
ICAPR
2001
Springer
15 years 2 months ago
Pattern Matching and Neural Networks Based Hybrid Forecasting System
In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...
Sameer Singh, Jonathan E. Fieldsend