Time Series Prediction with a Weighted Bidirectional Multi-stream Extended Kalman Filter

Author

Xiao Hu
Danil V. Prokhorov
Donald C. Wunsch, Missouri University of Science and TechnologyFollow

Abstract

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.

Recommended Citation

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

Department(s)

Electrical and Computer Engineering

International Standard Serial Number (ISSN)

0925-2312

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2007 Elsevier, All rights reserved.

Publication Date

01 Jan 2007