Time Series Prediction with a Weighted Bidirectional Multi-stream Extended Kalman Filter
We use a multi-stream extended Kalman filter for the CATS benchmark (Competition on Artificial Time Series), to train recurrent multilayer perceptrons. A weighted bidirectional approach is adopted to combine forward and backward predictions and to generate the final predictions on the missing points.
X. Hu et al., "Time Series Prediction with a Weighted Bidirectional Multi-stream Extended Kalman Filter," Neurocomputing, vol. 70, no. 13-15, pp. 2392-2399, Elsevier, Jan 2007.
The definitive version is available at https://doi.org/10.1016/j.neucom.2005.12.135
Electrical and Computer Engineering
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